# Happy Endpoint - full content > Complete text of the Happy Endpoint catalog: web-scraping APIs, bulk datasets, daily-tracked data feeds, and every published article. Generated from source, always current. Short index: https://happyendpoint.com/llms.txt API catalog (JSON): https://happyendpoint.com/api-catalog.json MCP access: https://happyendpoint.com/mcp.md Authentication: https://happyendpoint.com/auth.md Every page on this site is also available as markdown by appending `.md` to its URL, for example https://happyendpoint.com/library/bayut-api.md. --- # APIs (27) # UAE Real Estate API Bayut and PropertyFinder in one UAE real estate API - 450K+ Dubai and Abu Dhabi listings, agent profiles, agencies, and transaction records as JSON. - Page: https://happyendpoint.com/library/uae-realestate-api - RapidAPI: https://rapidapi.com/happyendpoint/api/uae-real-estate-api - RapidAPI host: `uae-real-estate-api.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: uae-real-estate-api.p.rapidapi.com` and `x-api-key: ` - Tags: historical-data, property-search, property-details, market-trends ## Features - Bayut and PropertyFinder Data - Property Search - Agent Search - Agency Search - Transaction History - Single API Key - Location Autocomplete - 450,000+ Listings ## Endpoints (10) - `GET /autocomplete` - Location search with auto-complete, returns location IDs and coordinates - `GET /search-properties` - Search properties for rent or sale across Bayut and PropertyFinder with 15+ filters - `GET /property-details` - Full property details including photos, amenities, floor plans, and agent info - `GET /search-agents` - Find real estate agents by name or location across both platforms - `GET /agent-details` - Full agent profile with contact info, service areas, and listing stats - `GET /agent-properties` - All properties listed by a specific agent - `GET /search-agencies` - Search real estate agencies or brokerages by name or location - `GET /agency-details` - Full agency or brokerage profile with listing and agent statistics - `GET /agency-properties` - All properties listed by a specific agency or brokerage - `GET /get-transactions` - Historical property transaction data with filters for type, bedrooms, and time period The UAE Real Estate API combines property data from both Bayut and PropertyFinder through a single, unified interface. Instead of maintaining separate integrations for each platform, you get access to over 450,000 UAE property listings using one API key and one consistent endpoint structure. ## How It Works Pass a location name (such as "Dubai Marina" or "Business Bay") and the platform parameter, and the API resolves the location to the correct platform-specific ID and returns results. You do not need to pre-fetch location IDs or learn different schemas for each platform. Switching between Bayut and PropertyFinder data is a single parameter change. ## What the API Covers **Property search** supports 15 or more filters including location, bedrooms, bathrooms, price range, area, property type, furnishing, completion status, and rental frequency. Each result includes full listing data: price, photos, amenities, agent contact info, and verification status. **Agent and agency search** works across both platforms. Find agents by name or location, retrieve their full profiles with contact details, and pull their active listings. The same applies to agencies and brokerages. **Transaction data** provides historical sales and rental records filterable by property type, bedrooms, time period, and sort order. This is the foundation for property valuation tools, investment research dashboards, and automated market reports. ## Example Queries Search apartments for rent in Dubai Marina: ``` GET /search-properties?platform=bayut&purpose=rent&location=Dubai Marina&property_type=apartment ``` Get transaction history for Palm Jumeirah sales: ``` GET /get-transactions?platform=bayut&transaction_type=sale&location=Palm Jumeirah&time_period=1y ``` Find agents in Business Bay: ``` GET /search-agents?platform=propertyfinder&location=Business Bay&purpose=buy ``` ## Coverage All UAE Emirates: Dubai, Abu Dhabi, Sharjah, Ajman, Ras Al Khaimah, Fujairah, and Umm Al Quwain. Popular areas include Dubai Marina, Downtown Dubai, Palm Jumeirah, JBR, Business Bay, JLT, Arabian Ranches, DIFC, Al Reem Island, Yas Island, and Saadiyat Island. ## Data Sources | Platform | Website | Listings | |---|---|---| | Bayut | bayut.com | 200,000+ listings | | PropertyFinder | propertyfinder.ae | 250,000+ listings | ## Daily-tracked feeds Beyond request-time data, two [data feeds](/data-feeds) track this market day by day and record what changed: - [PropertyFinder Dubai Agent Movement Feed](/data-feeds/propertyfinder-dubai-agent-movement) - 25,115 agents tracked daily, with the movement that reveals who is slowing down, going independent, or new to the market. - [PropertyFinder Dubai Listings and Price-Change Feed](/data-feeds/propertyfinder-dubai-price-changes) - every price drop, delisting and day-on-market across 801,459 listings. ## Further reading - [UAE real estate data sources compared: PropertyFinder, Bayut, and aggregators](/blog/uae-real-estate-data-sources-compared) ## Further reading - [UAE real estate data sources compared: PropertyFinder, Bayut, and aggregators](/blog/uae-real-estate-data-sources-compared) --- # Bayut UAE Data Bayut API for UAE property data - 500K+ Dubai and Abu Dhabi listings, agent and agency profiles, off-plan projects, and transaction history. - Page: https://happyendpoint.com/library/bayut-api - RapidAPI: https://rapidapi.com/happyendpoint/api/uae-real-estate3 - RapidAPI host: `uae-real-estate3.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: uae-real-estate3.p.rapidapi.com` and `x-api-key: ` - Tags: map-search, property-search, property-details, market-trends ## Features - Property Search - Off-Plan Projects - Agent Directory - Agency Search - Amenities Filter - Location Autocomplete - No Proxies Required - JSON Responses ## Endpoints (10) - `GET /autocomplete` - Search locations across Dubai and the UAE, returns location IDs and slugs - `GET /search-property` - Search properties for sale or rent with filters for location, price, bedrooms, and property type - `GET /search-new-projects` - Search off-plan properties and new development projects in Dubai - `GET /agent-search-by-name` - Find real estate agents by name, returns profile, agency, and listing statistics - `GET /agent-properties` - Retrieve all active property listings from a specific agent - `GET /agency-search` - Search real estate agencies by location - `GET /agency-search-by-name` - Find agencies by name, returns profile and listing count - `GET /agency-details` - Get full details for a specific real estate agency - `GET /agency-properties` - Retrieve all listings from a specific agency - `GET /amenities-search` - Search available amenities and the count of properties featuring each The Bayut API gives developers structured, real-time access to property listings, agents, agencies, and development projects from Bayut.com, the UAE's leading real estate portal. All responses are delivered in clean JSON with no proxies required. ## What You Can Access Property search covers the full UAE market. Filter listings by location, price range, bedrooms, bathrooms, property type, furnishing status, completion status, and amenities. Results include property title, price, area in square feet, photos, agent contact details, and verification status. Off-plan and new development projects are accessible through a dedicated endpoint, making this API a strong fit for platforms focused on Dubai property investment or pre-launch project tracking. Agent and agency data is available in depth. Search for brokers by name, retrieve their active listings, and pull full agency profiles including contact information and listing statistics. The `/amenities-search` endpoint returns all available amenity filters (swimming pool, gym, parking, balcony, security) alongside a count of how many listings include each. Pass these directly into `/search-property` to build advanced filtering interfaces. ## Use Cases - Real estate portals targeting the Dubai and UAE market - PropTech platforms that need a reliable property data feed without building or maintaining scrapers - Investment dashboards tracking Dubai property prices and off-plan opportunities - Lead generation tools surfacing agents and agencies in specific areas - Analytics platforms studying UAE property market trends ## Response Format All endpoints return structured JSON with consistent pagination support: ```json { "success": true, "data": { "properties": [...], "total": 1432, "page": 1, "totalPages": 58 } } ``` ## Coverage UAE-wide coverage including Dubai Marina, Downtown Dubai, Palm Jumeirah, Business Bay, JBR, JLT, Arabian Ranches, and thousands of other communities and buildings across Dubai, Abu Dhabi, and Sharjah. ## Daily-tracked feeds Beyond request-time data, two [data feeds](/data-feeds) track this market day by day and record what changed: - [PropertyFinder Dubai Agent Movement Feed](/data-feeds/propertyfinder-dubai-agent-movement) - 25,115 agents tracked daily, with the movement that reveals who is slowing down, going independent, or new to the market. - [PropertyFinder Dubai Listings and Price-Change Feed](/data-feeds/propertyfinder-dubai-price-changes) - every price drop, delisting and day-on-market across 801,459 listings. ## Further reading - [Bayut API: Dubai real estate data](/blog/bayut-api-dubai-real-estate-data) - [UAE real estate data sources compared](/blog/uae-real-estate-data-sources-compared) --- # PropertyFinder UAE Data PropertyFinder API for live UAE real estate data - 500K+ listings with price trends, agent data, and new projects, as structured JSON via RapidAPI. - Page: https://happyendpoint.com/library/propertyfinder-api - RapidAPI: https://rapidapi.com/happyendpoint/api/uae-real-estate-property - RapidAPI host: `uae-real-estate-property.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: uae-real-estate-property.p.rapidapi.com` and `x-api-key: ` - Tags: map-search, property-search, property-details, market-trends ## Features - Property Search - Agent Directory - Broker Database - Market Intelligence - Transaction History - Price Trends - New Projects - Commercial Listings - Developer Directory - Redis Caching ## Endpoints (15) - `GET /autocomplete-location` - Search locations, communities, or buildings, returns IDs and coordinates - `GET /search-property` - Search residential properties for rent or sale with 15+ filter options - `GET /search-commercial-rent` - Search commercial properties available for rent - `GET /search-commercial-buy` - Search commercial properties available for purchase - `GET /search-new-projects` - Find off-plan and new development projects - `GET /property-details` - Full listing details including description, floor plans, photos, and agent info - `GET /search-agents` - Find real estate agents by location or name with contact details - `GET /search-brokers` - Find real estate brokerages operating in specific areas - `GET /agent-properties` - All active listings from a specific agent - `GET /broker-properties` - All active listings from a specific brokerage - `GET /price-trend-of-location` - Historical price trend data for a location and property type - `GET /property-insight` - Community-level insights, average prices, and popularity metrics - `GET /get-transactions` - Historical sales and rental transaction records for an area - `GET /real-estate-developers` - List of active real estate developers in the UAE - `GET /communities` - List of communities sorted by popularity or affordability The PropertyFinder API provides real-time access to one of the UAE's largest property databases. With 500K or more live listings and support for residential, commercial, and off-plan properties, it is built for production-grade real estate applications. ## What You Can Access **Property search** covers the full residential and commercial market with 15 or more filters: location, price range, bedrooms, bathrooms, area size, property type, furnishing, completion status, and listing date. Each result includes rich listing data: photos, description, amenities, location, and agent contact information. **Market intelligence** endpoints give you price trend history by location and property type, community-level insights, and historical transaction data covering both sales and rentals. These are the building blocks for investment research tools, property valuation dashboards, and automated market reports. **Agent and broker directories** are built in. Search for agents by location or name, retrieve their full profiles with contact details, and pull their active listings. The same applies to brokerages. **Commercial listings** are accessible through dedicated endpoints for rent and sale, covering offices, retail units, warehouses, and other commercial property types across the UAE. **Developer and community data** rounds out the API. Pull a list of active UAE property developers, or browse communities sorted by affordability or popularity. ## Performance Responses are delivered via a RESTful JSON API with pagination and Redis caching for fast, consistent access under high load. ## Use Cases - UAE real estate portals and property search applications - Investment dashboards with price trend and transaction history data - Agent and broker directory platforms - PropTech tools requiring both commercial and residential market coverage - CRM systems that sync UAE property listings and agent data ## Coverage Dubai, Abu Dhabi, Sharjah, and all major UAE communities including Dubai Marina, Downtown Dubai, Palm Jumeirah, JBR, Business Bay, JLT, Al Reem Island, Yas Island, and Saadiyat Island. ## Daily-tracked feeds Beyond request-time data, two [data feeds](/data-feeds) track this market day by day and record what changed: - [PropertyFinder Dubai Agent Movement Feed](/data-feeds/propertyfinder-dubai-agent-movement) - 25,115 agents tracked daily, with the movement that reveals who is slowing down, going independent, or new to the market. - [PropertyFinder Dubai Listings and Price-Change Feed](/data-feeds/propertyfinder-dubai-price-changes) - every price drop, delisting and day-on-market across 801,459 listings. ## Further reading - [Building a property alerts app on the PropertyFinder API](/blog/building-property-alerts-app-propertyfinder-api) - [Scraping PropertyFinder data legally at scale](/blog/scraping-propertyfinder-data-legally-at-scale) --- # Rightmove UK API Rightmove API for UK property data - sale and rental listings, sold price history, new homes, and student accommodation, with full filtering. - Page: https://happyendpoint.com/library/rightmove-uk - RapidAPI: https://rapidapi.com/happyendpoint/api/rightmove-uk-real-estate-data/ - RapidAPI host: `rightmove-uk-real-estate-data.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: rightmove-uk-real-estate-data.p.rapidapi.com` and `x-api-key: ` - Tags: sales, rentals, sold-prices, student-housing ## Features - Sales Listings - Rental Listings - Sold Price History - New Homes - Student Housing - Commercial Properties - Estate Agent Search - Location Autocomplete - Property Detail Pages ## Endpoints (11) - `GET /auto-complete` - Location and keyword suggestions to power search bars - `GET /property-for-sale` - Search residential properties currently listed for sale - `GET /new-home-for-sale` - Search new-build and development homes for sale - `GET /property-to-rent` - Search residential properties available for rent - `GET /student-property-to-rent` - Search student accommodation available for rent - `GET /commercial/properties-to-rent` - Search commercial properties available for rent - `GET /commercial/properties-to-sale` - Search commercial properties available for purchase - `GET /house-prices/sold-house-prices` - Historical sold prices for properties in a given area - `GET /sold-house-prices/details` - Detailed information about a specific historical sale - `GET /property-details` - Full listing details for a single Rightmove property - `GET /estate-agents/list` - Find and list estate agents operating in a specific area The Rightmove UK API provides fast, reliable access to property data from Rightmove, the UK's largest property portal. With 11 endpoints, it covers the complete UK property market: residential sales, rentals, new homes, student accommodation, commercial properties, sold price history, and estate agent data. ## What the API Covers **Residential listings** are available for both sale and rent. Each listing includes price, address, photos, key property attributes (bedrooms, bathrooms, floor area), and agent details. Results are returned as structured JSON and support standard pagination. **Sold prices** provide historical transaction data for any area in the UK, useful for property valuation tools, investment analysis, and market research. The detail endpoint gives you specific information about individual historical sales. **New homes** have a dedicated endpoint returning newly built and off-plan properties from developers across the UK. This is useful for platforms targeting first-time buyers or new build investors. **Student accommodation** is separated into its own endpoint, covering houses, flats, and purpose-built student properties near universities. A useful differentiator for platforms serving the student rental market. **Commercial properties** are available for both rent and purchase, covering offices, retail units, industrial spaces, and other commercial types. **Estate agents** can be searched by area, returning agents operating in that market with profile and contact information. ## Coverage UK-wide coverage including England, Scotland, and Wales. Major cities, suburban areas, and rural locations are all included. ## Why Use This API The API is engineered for speed with low-latency responses and clean, predictable JSON output. The breadth of endpoints means you can build a comprehensive UK property application without sourcing data from multiple providers. Whether you need current listings, historical price data, or agent directories, it is all available through the same integration. ## Further reading - [Rightmove UK property data: API and dataset guide](/blog/rightmove-uk-property-data-api) --- # Sephora API Sephora scraper API for live product data - US catalog with brands, prices, star ratings, review counts, and store stock levels, as structured JSON. - Page: https://happyendpoint.com/library/sephora-api - RapidAPI: https://rapidapi.com/happyendpoint/api/real-time-sephora-api - RapidAPI host: `real-time-sephora-api.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: real-time-sephora-api.p.rapidapi.com` and `x-api-key: ` - Tags: reviews, ratings, stock, store-finder ## Features - Product Search - Product Reviews - Brand Directory - Category Browse - Real-Time Availability - Store Locator - Keyword Autocomplete - Sub-400ms Responses ## Endpoints (11) - `GET /auto-complete` - Product suggestions from partial search queries - `GET /search-by-keyword` - Advanced keyword search with filters across the Sephora catalog - `GET /search-by-category` - Fetch products by category ID - `GET /search-by-brand` - Retrieve products from a specific brand - `GET /brands-list` - Full list of brands available on Sephora - `GET /categories-list` - Root product categories - `GET /category-data` - Subcategories and metadata for a given category - `GET /product-details` - Full product data including images, ingredients, pricing, and specifications - `GET /product-reviews` - Customer reviews and ratings for a product - `GET /product-availability` - Store-level stock availability for a product - `GET /store-list` - Sephora store locations near a given location The Sephora API provides real-time access to product data, inventory, reviews, and store locations from Sephora.com. With 11 endpoints and sub-400ms response times, it is built for production-grade beauty and retail applications. ## What the API Covers **Product discovery** works through multiple entry points. Search by keyword to find products matching a query, browse by category to navigate the catalog structure, or filter by brand to retrieve a specific brand's full lineup. The autocomplete endpoint supports real-time search suggestions for search-as-you-type interfaces. **Product details** return comprehensive data for individual items: name, description, ingredients, pricing, product images, and full specifications. This level of detail is useful for beauty apps that need to surface ingredient lists or formulation details alongside standard product information. **Reviews and ratings** are available through the `/product-reviews` endpoint, returning customer ratings and written feedback. This data is well suited for recommendation engines, comparison tools, or any interface where social proof is part of the product display. **Inventory data** from `/product-availability` returns store-level stock status, allowing applications to show users where a specific product is currently available near their location. **Store locations** are accessible via geo-based queries, returning Sephora store details including addresses and proximity to a given point. ## Authentication Include these two headers with every request: - `X-RapidAPI-Key`: your RapidAPI key - `X-RapidAPI-Host`: `real-time-sephora-api.p.rapidapi.com` ## Use Cases - Beauty and skincare apps surfacing product details, ingredient lists, and reviews - E-commerce platforms building affiliate storefronts or comparison tools around Sephora's catalog - Market intelligence tools tracking pricing and availability across SKUs - AI-powered recommendation engines that need structured product metadata and customer review data - Price and inventory monitoring tools for brands or retail analysts ## Further reading - [Sephora product data for catalog and price monitoring](/blog/sephora-product-data-beauty-catalog-price-monitoring) --- # Morningstar API Morningstar API for financial data - real-time equity and ETF quotes, fundamentals, valuation metrics, and ESG risk ratings for research tools. - Page: https://happyendpoint.com/library/morningstar - RapidAPI: https://rapidapi.com/happyendpoint/api/morningstar13 - RapidAPI host: `morningstar13.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: morningstar13.p.rapidapi.com` and `x-api-key: ` - Tags: real-time-quotes, financials, etfs, esg-ratings ## Features - Real-Time Quotes - Financial Statements - ESG Risk Ratings - ETF and Fund Data - Valuation Metrics - Earnings Transcripts - Ownership Data - Dividend History ## Endpoints (8) - `GET /auto-complete` - Find performanceId or ticker for any stock, ETF, fund, or index - `GET /stock/details` - Key metrics, price data, and summary for a stock or fund - `GET /stock/financials` - Income statement, balance sheet, and cash flow data - `GET /stock/valuation` - Valuation ratios including P/E, P/B, and earnings yield - `GET /stock/dividends` - Historical dividend payments and yield data - `GET /stock/ownership` - Institutional and insider ownership structure - `GET /market/summary` - Real-time market overview including movers and sector performance - `GET /esg/ratings` - Morningstar ESG risk and sustainability ratings for a security The Morningstar API gives developers access to institutional-grade financial data covering stocks, ETFs, mutual funds, and global market indexes. It is designed for investment platforms, financial analysis tools, and market dashboards that require deep, structured financial data. ## What the API Covers **Real-time market data** includes live quotes, price charts, and market mover updates across equities, commodities, currencies, and indexes. The data covers global markets, not just US equities. **Financial fundamentals** are accessible through dedicated endpoints: income statement, balance sheet, and cash flow data for public companies. Valuation ratios (P/E, P/B, earnings yield, and others) are available separately, making it straightforward to build screeners or comparison tools. **Corporate intelligence** includes executive details, institutional and insider ownership structures, historical dividend payments, and earnings call transcripts. These are the data points that differentiate a serious research tool from a basic quote tracker. **ESG ratings** are Morningstar's own sustainability and risk scoring, integrated directly into the API. This is particularly useful for platforms targeting ESG-conscious investors or institutional clients with sustainability mandates. **ETF and fund data** covers holdings, performance history, and category classification, making the API suitable for fund comparison tools and portfolio analytics platforms. ## How to Get Started Use the `/auto-complete` endpoint to find the unique `performanceId` or ticker for any asset. Pass that identifier to specific endpoints like `/stock/details` or `/stock/financials` to retrieve the data you need. The auto-complete endpoint handles stocks, ETFs, funds, indexes, commodities, and currencies. ## Use Cases - Investment platforms requiring deep fundamental and real-time market data - Portfolio analytics and performance tracking tools - Financial screening and research applications - ESG-focused investment tools and reporting dashboards - Applications looking for an alternative to Bloomberg Terminal or similar commercial data providers ## Further reading - [Morningstar financial data API: equities, ETFs and ESG](/blog/morningstar-financial-data-api) --- # Ikea Pro API IKEA API for product data - 12,000+ items with live pricing, dimensions, ratings, category paths, and per-store stock levels across every market. - Page: https://happyendpoint.com/library/ikea-pro - RapidAPI: https://rapidapi.com/happyendpoint/api/ikea-api-pro/ - RapidAPI host: `ikea-api-pro.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: ikea-api-pro.p.rapidapi.com` and `x-api-key: ` - Tags: stock-check, catalog, store-finder, global-coverage ## Features - Keyword Product Search - Category Browse - Product Details - Store Locator - Multi-Country Support - 12,000+ Products - Real-Time Catalog - Category Filters ## Endpoints (6) - `GET /countries` - List of supported IKEA countries and regions - `GET /stores` - IKEA store locations and details for a given country - `GET /search-by-keyword` - Search IKEA products by keyword with optional filters - `GET /search-by-category` - Browse products within a specific category - `GET /filters` - Available search and category filters for refining results - `GET /product-details` - Full product data including images, pricing, dimensions, materials, and availability The IKEA Pro API provides real-time access to IKEA's product catalog, store data, and category structure across multiple countries. It covers 12,000 or more products with current pricing, availability, dimensions, and high-resolution images. ## What the API Covers **Product search** works by keyword or category. A keyword search lets you find products directly (searching for "BILLY bookcase" returns matching products with full metadata). Category-based search mirrors how IKEA's website is structured, letting you navigate the full catalog hierarchy from furniture categories down to individual items. **Product details** include everything needed to build a complete product page: images, current pricing, availability status, dimensions, materials, and product specifications. The data is structured for direct integration without additional processing. **Store data** covers IKEA locations by country, making it useful for store finder features or location-based availability queries. **Multi-country support** means you can localize queries by passing a country parameter. This is useful for apps that need to show region-specific pricing or availability. ## Use Cases - E-commerce and affiliate storefronts featuring IKEA products - Interior design and room planning apps that need product dimensions and images - Price comparison and price tracking tools across IKEA categories - Inventory monitoring systems for retail analytics - AI-powered furniture recommendation engines that need structured product metadata ## Further reading - [IKEA catalog data for furniture-retail apps](/blog/ikea-catalog-data-furniture-retail-apps) ## Disclaimer This API is built by HappyEndpoint and is not affiliated with or endorsed by IKEA. All data is sourced from publicly available product information. --- # Klarna Ecom API Klarna API for shopping data - multi-store price comparison and price history across Amazon, Walmart, Target and more, in 13 regions. - Page: https://happyendpoint.com/library/klarna-ecom - RapidAPI: https://rapidapi.com/happyendpoint/api/klarna7/ - RapidAPI host: `klarna7.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: klarna7.p.rapidapi.com` and `x-api-key: ` - Tags: price-history, multi-store, discount-tracking, comparison ## Features - Multi-Store Coverage - Price History Charts - Product Reviews - 13 Regions Supported - Cross-Platform Search - Deal Discovery - Category Intelligence - Store and Category Data ## Endpoints (9) - `GET /product-search` - Search products across multiple stores with filters and sorting - `GET /category-search` - Browse products within a specific category - `GET /product-details` - Full product metadata from multiple retailers - `GET /product-reviews` - User and professional reviews for a product - `GET /price-history` - Historical price chart for a product across multiple time intervals - `GET /stores` - List of stores available in the Klarna shopping ecosystem - `GET /categories` - Category structure and subcategories - `GET /deals` - Current deals and discounted products - `GET /keyword-suggestions` - Search keyword suggestions for product discovery The Klarna Ecom API aggregates product data, pricing, reviews, and deals from multiple top e-commerce platforms through Klarna's shopping ecosystem. With a single API, you can access data from stores including Amazon, Walmart, Best Buy, Target, and many more, across 13 supported regions. ## What the API Covers **Multi-store product search** is the core capability. A single query returns results from multiple retailers, making it practical for building comparison engines, deal finders, or shopping aggregators without managing separate API integrations per store. **Price history** is available at the product level with data across multiple time intervals. This makes it possible to build price trackers, alert systems, or discount pattern analysis tools without maintaining your own historical pricing database. **Product reviews** include both user-submitted ratings and written reviews, as well as professional review content where available. Related product groups are accessible alongside the main product data, useful for building "similar items" or "frequently compared" features. **Category and store intelligence** endpoints expose the full structure of Klarna's shopping ecosystem: store lists, category hierarchies, subcategories, cashback opportunities, and curated Klarna shopping experiences. This is the data layer needed for building structured navigation and browsing interfaces. **Deal discovery** surfaces currently discounted products and active deals across the ecosystem. ## Supported Regions The API supports 13 regions: Austria, Denmark, Finland, France, Germany, Ireland, Italy, Netherlands, Norway, Spain, Sweden, UK, and USA. All features are supported across all regions. Pass the `region` parameter to localize results; the default is `usa`. ## Use Cases - Price comparison websites and browser extensions - Shopping assistant apps and AI recommenders - Affiliate marketing and deal discovery platforms - Dropshipping research tools - E-commerce analytics and market intelligence platforms ## Further reading - [Klarna Ecom API: price comparison and price history](/blog/klarna-price-history-shopping-api) --- # Tesco Data API Tesco grocery API for UK and Ireland - 300K+ SKUs with live pricing, Clubcard offers, nutrition, promotions, and store-level availability as JSON. - Page: https://happyendpoint.com/library/tesco-data - RapidAPI: https://rapidapi.com/happyendpoint/api/tesco-data-api/ - RapidAPI host: `tesco-data-api.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: tesco-data-api.p.rapidapi.com` and `x-api-key: ` - Tags: product-search, categories, nutrition, clubcard-offers ## Features - UK Product Search - Ireland Product Search - Product Details - Nutritional Data - Category Browsing - Category Taxonomy - Pricing and Offers - 300,000+ SKUs ## Endpoints (7) - `GET /product-search-by-keyword` - Search Tesco UK products by keyword, e.g. milk, bread, electronics - `GET /product-details` - Full product data for a Tesco UK product by ID or URL - `GET /ireland-product-details` - Full product data for a Tesco Ireland product by ID or URL - `GET /category-page` - Paginated product listings for a Tesco UK category - `GET /ireland-category-page` - Paginated product listings for a Tesco Ireland category - `GET /get-category-id-for-uk` - Full category taxonomy for Tesco UK - `GET /get-category-ids-for-ireland` - Full category taxonomy for Tesco Ireland The Tesco Data API provides real-time product data from Tesco UK and Tesco Ireland, covering over 300,000 SKUs. It is designed for grocery, retail, and e-commerce applications that need structured product information including pricing, nutritional data, promotional offers, and category hierarchy. ## What the API Covers **Product search** lets you query the Tesco UK catalog by keyword, returning matching products with names, prices, promotional offers, images, and availability status. For category-based browsing, paginated category pages are available for both UK and Ireland, allowing you to replicate Tesco's catalog structure in your own application. **Product details** endpoints return comprehensive data for individual products: name, description, pricing, promotional tags, images, stock status, and full nutritional information. This level of detail makes the API suitable for shopping assistants and health-focused grocery apps where ingredient and nutrition data matter. **Category taxonomy** endpoints return the full hierarchical structure of Tesco's categories for both regions, which is useful for building navigation trees or for bulk data collection across specific product segments. **Ireland coverage** is included as a first-class feature. Dedicated endpoints handle Tesco Ireland product details and category browsing separately, so regional differences in product range and pricing are preserved. ## Use Cases - Price comparison tools and grocery deal alert apps - Retail analytics and competitive intelligence dashboards - AI shopping assistants that need structured grocery data - Consumer demand and behavior analysis platforms - E-commerce catalog aggregation and automation systems ## Coverage Tesco UK and Tesco Ireland. Covers food, beverages, household goods, health and beauty, electronics, and other Tesco product categories. ## Further reading - [Tesco grocery API: product, price and availability at scale](/blog/tesco-grocery-api-product-price-availability) - [Choosing an API for grocery stores](/blog/api-for-grocery-stores) --- # H&M API H&M API for fashion product data - global catalog with prices, colours, sizes, stock levels, supplier detail, and store locations, as clean JSON. - Page: https://happyendpoint.com/library/hm-api - RapidAPI: https://rapidapi.com/happyendpoint/api/h-m-hennes-mauritz1/ - RapidAPI host: `h-m-hennes-mauritz1.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: h-m-hennes-mauritz1.p.rapidapi.com` and `x-api-key: ` - Tags: trend-analysis, global-stores, product-search, supplier-data ## Features - Product Search - Category Browse - Store Locator - Supplier Details - Multi-Country Support - Search Autocomplete - JSON Responses - Near Real-Time Data ## Endpoints (6) - `GET /product-search` - Search H&M products by keyword with filters for size, color, fit, and material - `GET /auto-complete` - Real-time search suggestions for search-as-you-type experiences - `GET /categories` - Full H&M category hierarchy for organizing or filtering product data - `GET /countries` - List of supported countries and language codes for localization - `GET /stores` - H&M store locations by country including opening hours and departments - `GET /supplier-details` - Supplier and manufacturing information for specific H&M products The H&M API provides real-time access to product data, store locations, and supplier information from H&M's global catalog. It covers all key data points needed for fashion discovery tools, retail analytics platforms, and e-commerce applications targeting the H&M product range. ## What the API Covers **Product search** supports keyword queries with advanced filters including size, color, fit, material, and sorting options. Pagination is included, making it practical for loading large result sets. Autocomplete is available through a separate endpoint for search-as-you-type interfaces. **Category structure** is accessible through a dedicated endpoint that returns H&M's full product hierarchy. This is useful for building navigation trees, filtering interfaces, or for organizing a catalog by product type. **Store data** covers H&M locations worldwide, returning stores by country with addresses, opening hours, and available departments. Multi-country localization is supported through the `/countries` endpoint, which provides language codes and region-specific configuration. **Supplier details** is a distinctive feature of this API. It returns manufacturing and supplier information for specific products, covering factory names, locations, and production details. This is valuable for platforms focused on supply chain transparency, sustainability reporting, or ethical sourcing research. ## Use Cases - Fashion trend trackers and product discovery apps - Price comparison tools and availability monitors across H&M's global catalog - Retail analytics dashboards tracking H&M product data - AI styling assistants that need structured clothing metadata - Supply chain transparency platforms using the supplier endpoint - E-commerce and affiliate tools built around H&M products ## Further reading - [H&M fashion data API: catalog, pricing and stores](/blog/hm-fashion-data-api) --- # Kohls Data API Kohl's API for US retail data - product catalog with live pricing, promotions, ratings, customer reviews, Q&A, and store inventory as JSON. - Page: https://happyendpoint.com/library/kohls-data - RapidAPI: https://rapidapi.com/happyendpoint/api/kohls-com/ - RapidAPI host: `kohls-com.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: kohls-com.p.rapidapi.com` and `x-api-key: ` - Tags: reviews, inventory, q-and-a, pricing ## Features - Product Search - Product Details - Customer Reviews - Q and A Data - Category Tree - Store Locator - Pricing Data - Inventory Status ## Endpoints (6) - `GET /product-search` - Search Kohls.com products by keyword, returns listings with pricing and availability - `GET /product-details` - Full product information including specifications, pricing, and stock status - `GET /product-reviews` - Customer reviews and ratings for a specific product - `GET /product-qa` - Buyer questions and seller answers for a specific product - `GET /categories` - Full Kohls product category tree and subcategory structure - `GET /stores` - Kohls store locations with addresses and contact details The Kohls Data API provides programmatic access to product information, pricing, inventory, reviews, and store data from Kohls.com. It is designed for retail analytics tools, price tracking applications, e-commerce research platforms, and affiliate marketing solutions that need structured data from one of the largest US department store chains. ## What the API Covers **Product search** queries the Kohls catalog by keyword, returning matching products with names, prices, promotional pricing, and availability status. This is the starting point for most integrations. **Product details** go deeper, providing full product specifications, pricing, stock status, product images, and categorization data. This endpoint is useful for building complete product pages or enriching an existing dataset. **Customer reviews** and **Q&A data** are available as separate endpoints. Reviews return ratings and written feedback from verified buyers. The Q&A endpoint surfaces questions asked by prospective buyers alongside official answers, providing context that product descriptions alone may not cover. **Category tree** exposes the full hierarchical structure of Kohls' product taxonomy, useful for building category-level navigation or for systematic catalog collection. **Store locator** returns Kohls store locations with addresses and contact details, useful for applications that combine online and in-store data. ## Use Cases - Price comparison platforms tracking Kohls product prices and promotional deals - Retail analytics dashboards monitoring availability and pricing changes - E-commerce catalog enrichment and affiliate marketing tools - Market research and brand intelligence analysis - Inventory monitoring systems tracking stock changes over time ## Further reading - [Kohl's API: US retail product, review and store data](/blog/kohls-api-us-retail-product-data) --- # Priceline Pro API Priceline API for travel data - real-time hotel rates and availability, room-level pricing, flight search, and car rental rates from one endpoint. - Page: https://happyendpoint.com/library/priceline-pro - RapidAPI: https://rapidapi.com/happyendpoint/api/priceline-api-pro/playground - RapidAPI host: `priceline-api-pro.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: priceline-api-pro.p.rapidapi.com` and `x-api-key: ` - Tags: hotels, flights, cars, vacation-packages ## Features - Hotel Search - Hotel Details and Rooms - Real-Time Room Pricing - Flight Search - Car Rentals - Location Autocomplete - Real-Time Availability - Fast and Reliable ## Endpoints (6) - `GET /autocomplete-location-search` - Fast, predictive location search for hotels, airports, and destinations - `GET /hotels-search` - Search hotels by any criteria including location, dates, and occupancy - `GET /hotel-details` - Rich hotel details including photos, amenities, and policies - `GET /hotel-rooms-and-pricing-details` - All available room types with granular, real-time pricing - `GET /cars` - Search car rental options by pickup location and dates - `GET /flight` - Search flights by origin, destination, dates, and preferences The Priceline Pro API provides real-time access to travel data from Priceline.com, covering hotels, flights, and car rentals. It is built for developers who need fast, stable, and comprehensive travel data to power booking tools, price comparison engines, and travel applications. ## What the API Covers **Hotel search** returns available properties based on location, check-in and check-out dates, and occupancy requirements. The `/hotels-search` endpoint gives you a broad results set, while `/hotel-details` pulls rich data for any specific property: photos, amenity lists, policies, and ratings. **Room pricing** is a dedicated endpoint returning granular, real-time data for all available room types within a hotel. This level of detail is what separates a basic hotel search from a full booking-ready integration. Each room entry includes the room type, pricing, and availability at the time of the request. **Flight search** covers the data and parameters needed to build a flight search experience: origin, destination, dates, and preferences. Results reflect current availability and pricing directly from Priceline. **Car rentals** are available through the `/cars` endpoint, returning rental options at a specified pickup location with pricing per day. **Location autocomplete** powers the search experience by returning predictive destination suggestions as users type, covering hotels, airports, cities, and landmarks. ## Use Cases - Online travel agencies and booking platforms - Hotel and flight price comparison tools - Corporate travel management applications - AI travel assistants that need structured real-time pricing - Deal discovery apps targeting travelers looking for the best available rates ## Further reading - [Travel-rate aggregation with the Priceline API](/blog/priceline-api-travel-rate-aggregation-hotels) ## Disclaimer This API is an independent service built by HappyEndpoint. It is not affiliated with, endorsed, or sponsored by Priceline.com. All data is retrieved from publicly available sources. --- # Fotocasa API Fotocasa scraper API for Spain - 1.5M+ property listings across the mainland, Balearics and Andorra, with prices, photos, and granular filters. - Page: https://happyendpoint.com/library/fotocasa-api - RapidAPI: https://rapidapi.com/happyendpoint/api/fotocasa3 - RapidAPI host: `fotocasa3.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: fotocasa3.p.rapidapi.com` and `x-api-key: ` - Tags: map-search, analytics, property-details, market-trends ## Features - Property Search - Location Autocomplete - Detailed Listings - Market Analytics - Spain and Andorra Coverage - Balearic Islands - Real-Time Updates - RESTful JSON API ## Endpoints (3) - `GET /property-suggestions` - Search suggestions and autocomplete for locations and properties in Spain - `GET /search-properties` - Search property listings with filters for location, price, property type, and more - `GET /property-details` - Comprehensive listing data for a specific property The Fotocasa API provides access to one of Spain's largest real estate databases, with over 1.5 million property listings across Spain, Andorra, and the Balearic Islands. Data is updated continuously and delivered as clean JSON, making it straightforward to integrate into property search tools, market research platforms, and real estate applications. ## What the API Covers **Property search** supports filtering by location, price, property type, number of rooms, and other standard real estate parameters. The search suggestion endpoint powers autocomplete experiences, returning location suggestions and property matches as users type. **Listing data** is comprehensive. Each property record includes price, location, property type, size, photos, key specifications, and agent or developer information where available. **Market coverage** spans all of Spain's regions, from major urban centers like Barcelona and Madrid to coastal areas such as Costa del Sol and the Canary Islands. Andorra and the Balearic Islands are also included, which is relevant for international buyers and cross-border property platforms. ## Use Cases - Spanish real estate portals and property search applications - Market research and analysis tools for the Spanish property sector - Property valuation platforms using live listing data - Investment portfolio tools tracking Spanish real estate - Location intelligence and PropTech applications covering the Iberian market ## Authentication All requests require the standard RapidAPI headers: - `X-RapidAPI-Key`: your RapidAPI key - `X-RapidAPI-Host`: `fotocasa3.p.rapidapi.com` ## Further reading - [Fotocasa API: Spain real estate data](/blog/fotocasa-spain-real-estate-api) --- # Idealista API Idealista API for live property data across Spain, Italy, and Portugal - detailed listings, agent intelligence, and market analytics via RapidAPI. - Page: https://happyendpoint.com/library/idealista-api - RapidAPI: https://rapidapi.com/happyendpoint/api/idealista17 - RapidAPI host: `idealista17.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: idealista17.p.rapidapi.com` and `x-api-key: ` - Tags: real-estate, map-search, property-details, analytics ## Features - Advanced Property Search - AI-Powered Smart Search - Geo & ZIP-Based Search - Comprehensive Property Intelligence - Listing Analytics & Engagement - Agent & Agency Intelligence ## Endpoints (14) - `GET /auto-complete` - Location autocomplete by name prefix. - `GET /smart-search` - Natural-language search - server parses a free-text query into structured filter params. - `GET /sublocations` - Drill from a parent location to its direct children. - `GET /reverse-geocode` - Find points of interest closest to a latitude/longitude pair. - `GET /property-search` - Paginated property search by location. - `GET /property-search-by-url` - Paste any public Idealista search URL and get listings back in one call. - `GET /property-search-by-coordinates` - Search listings inside a circular area defined by latitude, longitude, and radius. - `GET /property-search-by-zip` - Search listings by postal code. - `GET /property-details` - Full property detail page (PDP). - `GET /property-details-by-url` - Paste any property URL and get the full property detail page back in one call. - `GET /listing-stats` - View counts and lead-engagement stats for a listing. - `GET /comments` - Listing description text for a property, auto-translated into the requested language. - `GET /agent-details` - Agency / agent profile: branding, contact, phone, active listings. - `GET /agent-listings` - Paginated listings published by a specific agency. The Idealista Data API allows developers to search properties, retrieve detailed listing information, analyze listing engagement, resolve property URLs, access agent intelligence, perform geo-based searches and build advanced real-estate applications using a clean and scalable interface. Whether you're building real-estate marketplaces, investment dashboards, relocation platforms, analytics systems, CRM integrations, lead generation tools, AI-powered housing applications, automation workflows, or map-based property experiences, this API provides reliable programmatic access to structured housing-market data across Spain, Italy, and Portugal. ## What the API Covers **Advanced Property Search** supports searching real-estate listings using flexible filters and structured search parameters, including city or region, price range, property type, bedrooms & bathrooms, rent or sale operation, keywords, and more. **AI-Powered Smart Search** lets you use natural-language and intent-based property discovery to simplify complex searches. **Geo & ZIP-Based Search** helps you search listings using ZIP codes, coordinates, and map-based location data. **Comprehensive Property Intelligence** retrieves detailed property information with structured listing metadata. Responses may include full descriptions, images & media, pricing information, geolocation data, energy certifications, amenities & features, publication dates, floor plans, virtual tours, and agent information. **Listing Analytics & Engagement Data** gives you access to listing engagement metrics and market-performance insights, such as visits, favorites, contacts, engagement metrics, listing activity, and user comments. **Agent & Agency Intelligence** retrieves structured information about agencies, agents and active listings, including agency branding, active listings, contact details, microsite information, and portfolio insights. ## Use Cases - **Real Estate Aggregators**: Build searchable property marketplaces with live listing data. - **Investment & Market Analytics**: Track pricing trends, analyze neighborhoods and identify opportunities. - **CRM & Internal Tools**: Sync property and agent information into internal workflows. - **AI & Automation**: Use structured real-estate data in LLMs, recommendation systems and automation pipelines. - **Relocation & Housing Apps**: Help users discover neighborhoods and homes using geo-search and autocomplete. - **Geo & Map Applications**: Build map-based property search experiences using coordinates and reverse geocoding. ## Authentication All requests require the standard RapidAPI headers: - `X-RapidAPI-Key`: your RapidAPI key - `X-RapidAPI-Host`: `idealista17.p.rapidapi.com` --- *Disclaimer: This API is an independent third-party service and is not affiliated with, endorsed by or sponsored by Idealista or Idealista S.A.U.* ## Further reading - [Idealista API: property data for Spain, Italy and Portugal](/blog/idealista-api-southern-europe-property-data) --- # PropertyFinder - Search by URL PropertyFinder API - pass any PropertyFinder search URL and get live UAE property listings back as structured JSON. No scraping to maintain. - Page: https://happyendpoint.com/library/propertyfinder-api-2 - RapidAPI: https://rapidapi.com/happyendpoint/api/propertyfinder1 - RapidAPI host: `propertyfinder1.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: propertyfinder1.p.rapidapi.com` and `x-api-key: ` - Tags: property-search, property-details, map-search, market-trends ## Features - URL to JSON Conversion - 500K+ Live Listings - Agent and Broker Contacts - Geo-Coordinates Included - Pagination Support - Redis Caching - Sub-500ms Latency - No Proxies Required ## Endpoints (2) - `GET /search-by-url` - Pass any PropertyFinder search URL and receive fully parsed listing data as JSON - `GET /property-details-by-url` - Retrieve full property details from a PropertyFinder listing URL The PropertyFinder Search by URL API converts any PropertyFinder search URL directly into structured JSON data. Instead of building or maintaining a scraper, you pass a URL and receive clean, parsed listing results ready to use in your application. ## How It Works Copy any search URL from PropertyFinder, including URLs with filters, page numbers, or sorting parameters applied, and pass it to the API endpoint. The response returns fully structured property data from that exact results page. This works with: - Filtered searches (price range, bedrooms, location, amenities) - Any page number for pagination through large result sets - Sorting and advanced query parameters already applied in the URL ## What Each Response Includes Every API response contains rich, structured data extracted from the listings: - Property details: price, size, bedrooms, bathrooms, property type - Full location hierarchy with geo-coordinates for mapping - Amenities list and furnishing status - High-quality images and media URLs - Agent and broker information including contact details - Listing metadata, verification status, and availability ## Why URL-Based Access The URL-based approach is particularly useful when: - Users paste PropertyFinder links directly into your tool (chatbots, CRMs, browser extensions) - You are processing a list of URLs collected from external sources - You want to mirror a specific search someone has already set up on PropertyFinder - You need to paginate through a filtered search without reconstructing filter parameters manually For standard programmatic property search, the main PropertyFinder UAE Data API offers a full parameter-based search interface. ## Performance Responses are delivered in under 500ms using Redis caching. No proxies are required and bot protection is handled server-side, so you get reliable access without managing infrastructure. ## Coverage Dubai, Abu Dhabi, Sharjah, and all UAE communities. Covers residential rentals and sales, commercial properties, and new development projects. Data is sourced in real time from PropertyFinder.ae. ## Daily-tracked feeds Beyond request-time data, two [data feeds](/data-feeds) track this market day by day and record what changed: - [PropertyFinder Dubai Agent Movement Feed](/data-feeds/propertyfinder-dubai-agent-movement) - 25,115 agents tracked daily, with the movement that reveals who is slowing down, going independent, or new to the market. - [PropertyFinder Dubai Listings and Price-Change Feed](/data-feeds/propertyfinder-dubai-price-changes) - every price drop, delisting and day-on-market across 801,459 listings. ## Further reading - [Scraping PropertyFinder data legally at scale](/blog/scraping-propertyfinder-data-legally-at-scale) - [Building a property alerts app on the PropertyFinder API](/blog/building-property-alerts-app-propertyfinder-api) ## Further reading - [Scraping PropertyFinder data legally at scale](/blog/scraping-propertyfinder-data-legally-at-scale) - [Building a property alerts app on the PropertyFinder API](/blog/building-property-alerts-app-propertyfinder-api) --- # 99.co Singapore API Live Singapore property data from 99.co. Search condos, HDB, rentals, and sale listings, plus new launches, transactions, price trends, and agents. - Page: https://happyendpoint.com/library/99co-api - RapidAPI: https://rapidapi.com/happyendpoint/api/99-co-sg-api - RapidAPI host: `99-co-sg-api.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: 99-co-sg-api.p.rapidapi.com` and `x-api-key: ` - Tags: property-search, property-details, new-projects, transactions, market-trends ## Features - Property Search - New Launch Projects - Transaction History - Price Trends - Nearby Amenities - Agent Directory - URL Resolver - Location Autocomplete ## Endpoints (14) - `GET /search-property` - Search Singapore sale and rental listings with rich filters - `GET /search-count` - Count listings matching a set of filters without pulling full results - `GET /listing-details` - Full listing detail by listing ID - `GET /listing-details-by-url` - Resolve full listing details from a 99.co listing URL - `GET /similar-listings` - Comparable listings for a given property - `GET /new-projects` - Browse new launch and upcoming condo developments with price ranges - `GET /project-details` - Full project detail with facilities, floor plans, and active sale and rent units - `GET /project-details-by-url` - Resolve project details from a 99.co project URL - `GET /project-nearby` - Nearby MRT, schools, supermarkets, parks, and commute times for a project - `GET /transactions` - Sold and rental transaction history for a project, area, or district - `GET /transaction-trends` - Price trends and summary statistics for a project, area, or district - `GET /agents` - Search the 99.co agent directory by name, agency, and contact - `GET /agent-details` - Full public agent profile with contact info and listings breakdown - `GET /autocomplete` - Find location and project IDs to use in search filters The 99.co Singapore API gives developers structured, real-time access to property listings, new launch projects, transactions, and agents from 99.co, one of Singapore's leading real estate portals. All responses are clean JSON, with no scraping infrastructure to build or maintain. ## What You Can Access Property search covers the full Singapore market: condos, HDB flats, landed homes, and apartments for sale or rent. Filter by location, price, property type, bedrooms, and more, then pull full listing details by ID or directly from a 99.co listing URL. The `/similar-listings` endpoint powers "similar homes" and comparable-property features. New launch and upcoming developments are available through a dedicated set of endpoints. Retrieve project facilities, floor plans, active sale and rent units, and nearby amenities including MRT stations, schools, supermarkets, and parks with walk, drive, and taxi commute times. Transaction and market data rounds out the API. Pull sold and rental transaction history for any project, area, or district, and get price trends with summary statistics for charts, valuation tools, and investment dashboards. ## Use Cases - Singapore property search and discovery apps - New launch and upcoming project tracking - Condo and HDB comparison platforms - Investment dashboards and rental yield tools - Transaction history and price trend analysis - Agent directory and lead generation tools ## Coverage Nationwide Singapore coverage across the HDB towns and private residential market, including districts such as Orchard, Bukit Timah, Marina Bay, Punggol, Tampines, and Jurong. ## Related APIs Building across Asia-Pacific or other regions? See the [SUUMO Japan Real Estate API](/library/suumo-api) for Japan, or browse every real estate source on our [Real Estate Data hub](/real-estate-data) and the full [API Library](/library). ## Further reading - [99.co API: Singapore property data](/blog/99co-api-singapore-property-data) --- # Aqar Saudi Arabia API Saudi Arabia real estate data from Aqar. Property search, AI natural-language search, district pricing, geographic reference data, and developer projects. - Page: https://happyendpoint.com/library/aqar-api - RapidAPI: https://rapidapi.com/happyendpoint/api/aqar - RapidAPI host: `aqar.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: aqar.p.rapidapi.com` and `x-api-key: ` - Tags: property-search, ai-search, market-trends, geo-data, developers ## Features - Property Search - AI Natural-Language Search - District Price Stats - Residential Indicators - Geographic Reference Data - Developer and Project Data - Reverse Geocoding - Location Autocomplete ## Endpoints (22) - `GET /search` - Search Saudi real estate listings with rich filters - `GET /ai-search` - Natural-language search that converts queries into structured filters and listings - `GET /related-listings` - Listings similar to a given one - `GET /autocomplete` - Location autocomplete with place suggestions - `GET /place-bounds` - Resolve a place ID into a bounding box - `GET /listing-details` - Full single-listing detail by ID - `GET /listing-details-by-url` - Full listing detail from a listing URL - `GET /listing-views` - View count for a listing - `GET /categories` - Property-category taxonomy - `GET /cities` - Cities with per-category listing counts - `GET /districts` - Districts within a city - `GET /directions` - Direction and zone breakdown of a city - `GET /admin-regions` - Administrative regions and provinces of Saudi Arabia - `GET /reverse-geocode` - Resolve coordinates into city, district, and direction IDs and names - `GET /district-price-stats` - Per-district price and transaction time series - `GET /residential-indicators` - Latest residential price indicator for a district - `GET /district-rating` - District quality rating and resident comments - `GET /moj-categories` - Ministry of Justice category mapping - `GET /project-details` - Full off-plan or ready project detail - `GET /developer-details` - Real estate developer profile - `GET /developer-projects` - Paginated projects for a developer - `GET /projects-by-city` - Cities ranked by project count The Aqar Saudi Arabia API provides structured access to real estate data from Aqar, the Kingdom's leading property marketplace. Search listings, analyse district-level pricing, work with Saudi geographic reference data, and explore developers and projects, all through clean JSON endpoints. ## What You Can Access Property search supports rich filters across location, property type, category, price range, and area. Beyond the standard `/search`, the `/ai-search` endpoint accepts natural-language queries such as "3 bedroom villa in Riyadh under 2 million SAR" and converts them into structured filters plus matching listings. Retrieve full listing details by ID or URL, related listings, and per-listing view counts. Geographic and reference data is a first-class part of the API. Pull administrative regions, cities, districts, and direction breakdowns, resolve coordinates with reverse geocoding, and translate between category taxonomies including the Ministry of Justice mapping. Market intelligence covers district price statistics and time series, the latest residential price indicators, and district quality ratings with resident comments. Developer and project endpoints let you explore off-plan and ready projects, developer profiles, and city-level project distribution. ## Use Cases - Proptech platforms and property portals for Saudi Arabia - AI-powered property assistants and search copilots - Investment analysis and district-level market research - Valuation models built on district pricing and indicators - Location intelligence and mapping products ## Coverage Nationwide Saudi Arabia coverage across major cities including Riyadh, Jeddah, Dammam, Mecca, and Medina, with district-level detail and administrative region data. ## Related APIs Working across the region? The [Bayut UAE Data API](/library/bayut-api) and [UAE Real Estate API](/library/uae-realestate-api) cover the Gulf market. Browse every source on our [Real Estate Data hub](/real-estate-data) or the full [API Library](/library). ## Further reading - [Aqar API: Saudi Arabia property data and district pricing](/blog/aqar-api-saudi-arabia-property-data) --- # Hepsiemlak Turkey API Turkey real estate data from Hepsiemlak. Search property listings by city and district, get details, filters, similar listings, and market price index. - Page: https://happyendpoint.com/library/hepsiemlak-api - RapidAPI: https://rapidapi.com/happyendpoint/api/hepsiemlak-turkish-property-api - RapidAPI host: `hepsiemlak-turkish-property-api.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: hepsiemlak-turkish-property-api.p.rapidapi.com` and `x-api-key: ` - Tags: property-search, property-details, market-trends, locations ## Features - Property Search - Search by URL - Listing Details - Similar Properties - City, County, and District Data - Location Autocomplete - Search Filters - Market Price Index ## Endpoints (11) - `GET /search-property` - Search Türkiye property listings with rich filters - `GET /search-by-url` - Run a search from a Hepsiemlak search URL - `GET /property-details` - Full listing detail by property ID - `GET /property-details-by-url` - Listing detail from a Hepsiemlak property URL - `GET /similar-properties` - Similar property listings for a given listing - `GET /locations-autocomplete` - Find location, firm, and project search slugs - `GET /cities` - All Turkish provinces with IDs - `GET /counties` - Counties for a selected city - `GET /districts` - Districts for a selected county - `GET /search-filters` - Valid filter values and taxonomy for a category - `GET /price-index` - Market price index and time series for a location The Hepsiemlak Turkey API provides structured access to Türkiye real estate data from Hepsiemlak, one of the leading property platforms in the country. Search listings, retrieve full details, work with Turkish location data, and analyse market price trends through clean JSON endpoints. ## What You Can Access Property search covers homes for sale and rent across Türkiye with rich filters. Run a query directly or resolve a Hepsiemlak search URL, then pull full listing details by property ID or by URL. The `/similar-properties` endpoint returns comparable listings as full cards for recommendation and "similar homes" features. Location data is structured hierarchically: list all Turkish provinces (`/cities`), drill into counties and districts, and use `/locations-autocomplete` to resolve location, firm, and project search slugs. The `/search-filters` endpoint returns valid filter values and taxonomy for a given category so you can build accurate advanced-search UIs. Market intelligence comes from `/price-index`, which returns market price index data and a time series for a location, useful for pricing tools, dashboards, and investment research. ## Use Cases - Real estate search apps for the Turkish market - Property listing aggregators - Türkiye housing market dashboards and price analysis - Lead generation and property monitoring tools - Location-based property intelligence ## Coverage Nationwide Türkiye coverage across provinces, counties, and districts, including major markets such as Istanbul, Ankara, Izmir, Antalya, and Bursa. ## Related APIs Comparing European and regional markets? See the [Fotocasa API](/library/fotocasa-api) for Spain and the [Njuškalo Croatia API](/library/njuskalo-api) for the Balkans. Browse every source on our [Real Estate Data hub](/real-estate-data) or the full [API Library](/library). ## Further reading - [Turkey real estate data: Hepsiemlak and Emlakjet compared](/blog/hepsiemlak-emlakjet-turkey-property-data) --- # Njuškalo Croatia API Marketplace data from Njuškalo, Croatia's largest classifieds site. Search cars, real estate, and listings, plus sellers, categories, and pricing. - Page: https://happyendpoint.com/library/njuskalo-api - RapidAPI: https://rapidapi.com/happyendpoint/api/njuskalo - RapidAPI host: `njuskalo.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: njuskalo.p.rapidapi.com` and `x-api-key: ` - Tags: marketplace, classifieds, cars, real-estate, sellers ## Features - Marketplace Search - Category Browsing - Listing Details - Similar Listings - Seller Profiles and Reviews - Trending Categories - Geocoding - URL Parser ## Endpoints (20) - `GET /search-suggestions` - Search typeahead suggestions - `GET /search` - Search listings with free text and filters - `GET /search-count` - Count listings matching a filter - `GET /search-by-category` - Browse and filter listings within a category - `GET /latest` - Newest listings on the marketplace - `GET /similar-listings` - Listings similar to a given ad - `GET /listing-details` - Full single-listing detail by ID - `GET /listing-details-by-url` - Full listing detail from a listing URL - `GET /listing-overview` - Bundle of listing detail, similar listings, and seller in one call - `GET /parse-url` - Parse any Njuškalo URL into kind and ID - `GET /category-navigation` - Sub-category navigation tree - `GET /category-detail` - Look up categories by ID - `GET /filter-options` - Available filters and values for a category - `GET /recommended-categories` - Recommended categories with sample ads - `GET /trending-categories` - Currently trending categories - `GET /popular-brands` - Popular marketplace brands - `GET /geocode` - Address and locality autocomplete - `GET /reverse-geocode` - Resolve coordinates into a locality hierarchy - `GET /seller-profile` - Public seller or store profile with ratings - `GET /seller-reviews` - Public buyer reviews for a seller The Njuškalo Croatia API provides structured access to marketplace data from Njuškalo, Croatia's largest online classifieds platform. Search and browse listings across thousands of categories, pull detailed advertisement and seller data, and tap into category and location intelligence, all as clean JSON. ## What You Can Access Njuškalo spans cars (automobili), motorcycles, real estate (nekretnine), electronics, jobs, services, boats, and general classifieds (oglasi). Search with free text and filters, browse within a specific category, surface the newest or trending listings, and return typeahead suggestions and similar ads. Listing endpoints return full advertisement detail by ID or URL, or a single `/listing-overview` bundle combining detail, similar listings, and seller information in one call. The `/parse-url` endpoint turns any Njuškalo URL into a kind and ID for URL-driven workflows. Category and marketplace intelligence includes the sub-category navigation tree, category lookup by ID, available filters and values, recommended and trending categories, and popular brands. Geocoding and reverse geocoding resolve addresses and coordinates into localities, and seller endpoints return public store profiles, ratings, and buyer reviews. ## Use Cases - Marketplace and classifieds aggregators - Automotive intelligence and vehicle price monitoring - Real estate portals sourcing Croatian listings - Price monitoring and competitive analysis - Market research across Croatia's marketplace ecosystem - AI shopping assistants and recommendation engines ## Coverage Nationwide Croatia coverage across all Njuškalo categories, from vehicles and real estate to electronics, jobs, and consumer goods, with seller and location detail. ## Related APIs Njuškalo is part of our [Aggregator](/categories/aggregator) catalog. For dedicated real estate sources, see the [Hepsiemlak Turkey API](/library/hepsiemlak-api) or browse the full [API Library](/library). ## Further reading - [Classifieds API guide: Njuskalo and Gumtree marketplace data](/blog/classifieds-api-njuskalo-gumtree-marketplace-data) --- # SUUMO Japan Real Estate API Japan real estate data from SUUMO. Search rentals and sales, station and commute-based discovery, plus address, railway, and agency reference data. - Page: https://happyendpoint.com/library/suumo-api - RapidAPI: https://rapidapi.com/happyendpoint/api/suumo-japan-real-estate - RapidAPI host: `suumo-japan-real-estate.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: suumo-japan-real-estate.p.rapidapi.com` and `x-api-key: ` - Tags: property-search, property-details, rentals, commute-search, geo-data ## Features - Rental and Sale Search - Unified Search - Station and Commute Search - Property Details - New Condo Data - Nearby Facilities (GeoJSON) - Address and Postal Lookup - Agency Profiles ## Endpoints (21) - `GET /search-sale` - Search buy and sell listings across condos, houses, and land - `GET /search-rentals` - Search rental listings with rich filters - `GET /search-count` - Per-ward or per-station match counts for a prefecture - `GET /unified-search` - Cross-type search via the unified matching engine - `GET /unified-search-count` - Hit count from the unified matching engine - `GET /property-details` - Full detail for a buy or sell listing including condo, house, or land - `GET /rental-details` - Full detail for a rental listing - `GET /new-condo-details` - Full detail for a new-condo project - `GET /property-by-url` - Resolve full property detail from a SUUMO URL - `GET /parse-url` - Inspect a SUUMO URL to extract kind and codes without fetching detail - `GET /listing-overview` - Bundle rental detail, popularity, similar listings, and agency in one call - `GET /popularity` - Inquiry and popularity count for a rental listing - `GET /similar-rentals` - Rentals similar to a given rental - `GET /similar-properties` - Listings similar to a given buy or used-house property - `GET /cities` - City and ward list for a prefecture - `GET /railway-stations` - Railway line and station master data for a prefecture - `GET /address-master` - Nationwide address and area master data - `GET /postal-code` - Convert a postal code into address data - `GET /commute-search` - Stations reachable within a given time and transfer limit - `GET /nearby-facilities` - Facility and POI points in a lat/lng bounding box as GeoJSON - `GET /agency` - Real estate company or shop profile by company code The SUUMO Japan Real Estate API provides structured, real-time access to rental and buy/sell listings, station data, commute-based discovery, and agency information from SUUMO, one of Japan's largest property portals. Japanese property search depends heavily on railway access and commute time, and this API is built around those real-world requirements. ## What You Can Access Search rentals or sale listings (condos, houses, and land) with rich filters, or use the unified matching engine for cross-type search. Count-based endpoints return per-ward and per-station match counts for a prefecture, ideal for filter previews and market sizing. Retrieve full detail for rentals, buy/sell listings, and new-condo projects, or resolve any SUUMO URL into structured detail with `/property-by-url` and `/parse-url`. Station and commute search is a core strength. Pull railway line and station master data for a prefecture, and use `/commute-search` to find stations reachable within a chosen travel time and transfer count, powering relocation and apartment-search tools. City, ward, address master, and postal-code lookups round out the geographic reference data, and `/nearby-facilities` returns POI points in a bounding box as GeoJSON. Recommendation endpoints surface similar rentals and similar buy/used-house properties, `/popularity` returns inquiry counts, and `/agency` returns real estate company and shop profiles by company code. ## Use Cases - Japan real estate search and comparison apps - Relocation and commute-based home search tools - Station-based and map-based property discovery - Rental trend and market analytics - Neighborhood intelligence using nearby facilities - Real estate agency directories ## Coverage Nationwide Japan coverage across prefectures, cities, and wards, including major markets such as Tokyo, Osaka, Kyoto, Yokohama, Nagoya, and Fukuoka, with railway station and address-level reference data. ## Related APIs Building property search across other markets? See the [99.co Singapore API](/library/99co-api) for Singapore, or browse every real estate source on our [Real Estate Data hub](/real-estate-data) and the full [API Library](/library). ## Further reading - [SUUMO API: Japan real estate data](/blog/suumo-api-japan-real-estate-data) --- # Emlakjet Turkey API Turkey real estate data from Emlakjet. Search property listings, get details and price history, plus nearby places, demographics, agencies, and new projects. - Page: https://happyendpoint.com/library/emlakjet-api - RapidAPI: https://rapidapi.com/happyendpoint/api/emlakjet - RapidAPI host: `emlakjet.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: emlakjet.p.rapidapi.com` and `x-api-key: ` - Tags: property-search, property-details, price-history, locations, agencies ## Features - Property Search - Search by URL - Listing Details - Similar Listings - Price History - Nearby Places - Area Demographics - Province, District, and Neighborhood Data - Location Autocomplete - Search Filters and Categories - Agency Profiles and Listings - New Construction Projects ## Endpoints (18) - `GET /search-property` - Search Türkiye property listings with rich filters - `GET /search-by-url` - Run a search from an Emlakjet search URL - `GET /property-details` - Full listing detail by property ID - `GET /property-details-by-url` - Listing detail from an Emlakjet property URL - `GET /similar-listings` - Comparable listings for a given property - `GET /price-history` - Historical price changes for a listing - `GET /nearby-places` - Schools, hospitals, transport, and other nearby amenities - `GET /area-demographics` - Neighbourhood demographic and area information - `GET /locations-autocomplete` - Location autocomplete for building search experiences - `GET /cities` - All 81 Turkish provinces - `GET /districts` - Districts for a selected province - `GET /neighborhoods` - Neighbourhoods for a selected district - `GET /categories` - Property category taxonomy - `GET /search-filters` - Valid filter values and taxonomy for a category - `GET /agents-autocomplete` - Search real estate agencies and offices - `GET /agency-listings` - Agency profile and its active listings - `GET /project-search` - Search new housing projects and developers - `GET /project-details` - Detailed information for a construction project The Emlakjet Turkey API provides structured access to Türkiye real estate data from Emlakjet, one of the country's largest property marketplaces. Search listings with advanced filters, retrieve complete property details, analyse price history, and explore locations, agencies, and new construction projects through clean JSON endpoints. ## What You Can Access Property search covers apartments, houses, villas, land, commercial units, residences, and buildings across Türkiye, for sale, for rent, and daily rental. Run a query with dozens of filter options or resolve an existing Emlakjet search URL, then pull complete listing details by property ID or by URL, including media, specifications, location, and pricing. The `/similar-listings` endpoint returns comparable properties for recommendation features. Price intelligence comes from `/price-history`, which returns historical price changes for an individual listing, useful for tracking asking-price movement and negotiation research. Around each property, `/nearby-places` surfaces schools, hospitals, transportation, shopping, and other points of interest, while `/area-demographics` returns neighbourhood demographic and area information. Location data is structured hierarchically across all 81 provinces, their districts, and neighbourhoods, with `/locations-autocomplete` for typeahead search. The `/categories` and `/search-filters` endpoints return the full taxonomy and valid filter values so you can build accurate advanced-search UIs. Agency and project endpoints cover agency and office search, agency profiles with active listings, new housing project search by developer, and detailed project information. ## Use Cases - Real estate search apps for the Turkish market - Property listing aggregators - Investment analysis and price movement tracking - Proptech and CRM enrichment - Neighbourhood and location intelligence tools - New construction and developer research ## Coverage Nationwide Türkiye coverage across all 81 provinces, districts, and neighbourhoods, including major markets such as Istanbul, Ankara, Izmir, Antalya, and Bursa. ## Related APIs Also covering Türkiye is the [Hepsiemlak Turkey API](/library/hepsiemlak-api). For nearby markets, see the [Fotocasa API](/library/fotocasa-api) for Spain and the [Njuškalo Croatia API](/library/njuskalo-api) for the Balkans. Browse every source on our [Real Estate Data hub](/real-estate-data) or the full [API Library](/library). ## Further reading - [Turkey real estate data: Hepsiemlak and Emlakjet compared](/blog/hepsiemlak-emlakjet-turkey-property-data) --- # Yad2 Israel API Israel marketplace data from Yad2. Search real estate, vehicles, and second-hand listings, get details and maps, plus government-registered sale prices. - Page: https://happyendpoint.com/library/yad2-api - RapidAPI: https://rapidapi.com/happyendpoint/api/yad21 - RapidAPI host: `yad21.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: yad21.p.rapidapi.com` and `x-api-key: ` - Tags: marketplace, classifieds, real-estate, vehicles, sale-prices ## Features - Real Estate Search - Map View and Clusters - Listing Details - Government-Registered Sale Prices - Nearby Deals (Comps) - New Construction Projects - Agency and Dealer Ads - Vehicle Search - Vehicle Catalog and Models - Marketplace Listings - Location Autocomplete - Regions, Cities, and Neighborhoods ## Endpoints (24) - `GET /realestate-search` - Search Israel property listings for sale, rent, and commercial with rich filters - `GET /realestate-map` - Map view listing markers for a real estate filter set - `GET /realestate-map-clusters` - Area cluster counts (map aggregates) for a real estate filter set - `GET /realestate-details` - Full real estate ad detail by token - `GET /realestate-details-by-url` - Real estate ad detail from a listing URL - `GET /realestate-search-options` - Filter option lists for real estate search - `GET /realestate-agency-promos` - Agency banner cards and promoted agency listings for a search area - `GET /realestate-yad1-projects` - New-construction promos and project markers for a search area - `GET /realestate-yad1-nearby` - New-construction projects and promo ads related to a listing - `GET /latest-deals` - Recent government-registered completed deals with actual sale prices - `GET /realestate-nearby-deals` - Recent registered sale prices (comps) around a listing - `GET /vehicles-search` - Search vehicle listings with manufacturer, model, and range filters - `GET /vehicles-details` - Full vehicle ad detail by token - `GET /vehicles-details-by-url` - Vehicle ad detail from a listing URL - `GET /vehicles-catalog` - Manufacturer, model, and sub-model catalog with IDs for vehicle search - `GET /vehicles-models` - Model master data with price ranges and sub-models - `GET /vehicles-agency-ads` - More ads from the same dealer or agency as a vehicle listing - `GET /marketplace-listings` - Second-hand goods listings feed - `GET /marketplace-details` - Full second-hand product detail by token - `GET /locations-autocomplete` - Find city, area, neighborhood, and street IDs for searching - `GET /regions` - The 8 Yad2 regions used in real estate search - `GET /cities` - Cities, optionally within a region - `GET /neighborhoods` - Neighborhoods of a city - `GET /categories` - Full category and sub-category tree across all verticals The Yad2 Israel API provides structured access to Israel's largest classifieds platform. Search real estate, vehicles, and second-hand marketplace listings, retrieve complete ad details, and tap into location data and government-registered sale prices through clean JSON endpoints. ## What You Can Access Real estate search covers for-sale, rental, and commercial listings across Israel, with filters for price, rooms, floor, size, and amenities such as balcony, elevator, parking, and shelter. Map endpoints return listing markers and area cluster counts for building map-based search experiences, and `/realestate-search-options` returns valid filter values. Listing detail is available by token or directly from a Yad2 URL, and agency promo and new-construction (Yad1) endpoints surface promoted agencies and developer projects around a search area or listing. Price intelligence is a standout: `/latest-deals` returns recent government-registered completed deals with actual sale prices, and `/realestate-nearby-deals` returns registered sale prices around a specific listing, giving you real transaction comps rather than asking prices. The vehicles vertical covers cars, motorcycles, and more, with search by manufacturer, model, and price ranges, full ad detail by token or URL, a complete manufacturer-to-sub-model catalog, model master data with price ranges, and additional ads from the same dealer. The marketplace vertical returns second-hand goods feeds and full product detail. Location data is structured across Yad2's 8 regions, cities, neighborhoods, and streets, with `/locations-autocomplete` for typeahead search and `/categories` returning the full category tree across all verticals. ## Use Cases - Real estate search apps and portals for the Israeli market - Investment analysis with registered sale-price comps - Automotive intelligence and vehicle price monitoring - Marketplace aggregators and price monitoring - Proptech and CRM enrichment - Israeli market research across real estate, vehicles, and goods ## Coverage Nationwide Israel coverage across all 8 Yad2 regions, cities, neighborhoods, and streets, including Tel Aviv, Jerusalem, Haifa, and Be'er Sheva, spanning real estate, vehicles, and second-hand marketplace categories. ## Related APIs For another multi-vertical classifieds source, see the [Njuškalo Croatia API](/library/njuskalo-api) or the [Gumtree UK API](/library/gumtree-api). For dedicated property markets, browse our [Real Estate Data hub](/real-estate-data) or the full [API Library](/library). ## Further reading - [Yad2 API: Israel property, vehicle and marketplace data](/blog/yad2-api-israel-property-vehicle-data) --- # Auction.com API US distressed property data from Auction.com. Search foreclosure, bank-owned, and auction listings, get property details, schedules, and live bid status. - Page: https://happyendpoint.com/library/auction-com-api - RapidAPI: https://rapidapi.com/happyendpoint/api/auction-com-real-estate-api - RapidAPI host: `auction-com-real-estate-api.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: auction-com-real-estate-api.p.rapidapi.com` and `x-api-key: ` - Tags: real-estate, foreclosure, auctions, property-search, property-details ## Features - Advanced Property Search - ZIP Code Search - Search by URL - Upcoming Auctions - Listing Details - Auction Schedules and Venues - Live Auction and Bid Status - Location Autocomplete - Recommended Listings - Filter Taxonomies and Enums ## Endpoints (12) - `GET /advance-search` - Search US auction, foreclosure, and bank-owned listings with rich filters - `GET /search-by-zipcode` - Search listings in a 5-digit ZIP code - `GET /search-by-url` - Run a search from an Auction.com search URL - `GET /upcoming-auctions` - Upcoming auctions in chronological order, soonest first - `GET /listing-details` - Full listing detail by ID - `GET /listing-details-by-url` - Listing detail from a listing URL - `GET /auction-details` - Auction schedule, venue, trustee, live bid state, and property summary - `GET /auction-status` - Live auction and bid state for a listing - `GET /locations-autocomplete` - Find city, county, and ZIP values to search by - `GET /recommended-listings` - Curated recommendation rows of listings - `GET /marketing-tags` - Marketing tag taxonomy for the marketing_tags filter - `GET /enums` - All accepted filter values and response-field vocabularies The Auction.com API provides structured access to US distressed real estate from Auction.com, the largest online marketplace for foreclosure, bank-owned (REO), and auction properties. Search nationwide inventory, retrieve full property and auction details, and track live bid activity through clean JSON endpoints. ## What You Can Access Property search runs nationwide through `/advance-search` with filters for state, city, county, ZIP, beds, baths, square footage, price, occupancy status, auction format, financing availability, interior access, broker co-op, property type, and product type. You can also search within a single ZIP code or resolve an existing Auction.com search URL into results, and `/locations-autocomplete` returns valid city, county, and ZIP values for building search UIs. Listing endpoints return full property detail by ID or by URL, including specifications, media, and pricing. Auction-centric data is where this API stands apart: `/auction-details` bundles the auction schedule, venue, trustee, live bid state, and property summary in one call, `/auction-status` returns live auction and bid state for tracking active sales, and `/upcoming-auctions` lists what is going under the hammer next in chronological order. Supporting endpoints include curated recommendation rows, the marketing tag taxonomy (for flags like "Hot Property" or "Just Added"), and a complete `/enums` reference of accepted filter values and response-field vocabularies. ## Use Cases - Foreclosure and distressed-property investment tools - Auction tracking and bid monitoring dashboards - Real estate lead generation for investors and agents - Below-market-value deal discovery and alerting - REO and bank-owned inventory analysis - US housing market distress research ## Coverage Nationwide US coverage across all 50 states, spanning foreclosure sales, bank-owned (REO) inventory, and online and in-person property auctions. ## Related APIs For traditional listing markets, see the [Rightmove UK API](/library/rightmove-uk) or the [UAE Real Estate API](/library/uae-realestate-api). Browse every property source on our [Real Estate Data hub](/real-estate-data) or the full [API Library](/library). ## Further reading - [Foreclosure and auction property data](/blog/foreclosure-data-api-auction-com) --- # Gumtree UK API UK classifieds data from Gumtree. Search listings with filters, get ad details, seller profiles and reviews, plus categories, locations, and trends. - Page: https://happyendpoint.com/library/gumtree-api - RapidAPI: https://rapidapi.com/happyendpoint/api/gumtree2 - RapidAPI host: `gumtree2.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: gumtree2.p.rapidapi.com` and `x-api-key: ` - Tags: marketplace, classifieds, sellers, categories, locations ## Features - Listing Search - Search by URL - Search Suggestions - Trending Searches - Listing Details - Similar Listings - Seller Profiles, Listings, and Reviews - Category Tree and Filters - Location Autocomplete - Reverse Geocoding ## Endpoints (16) - `GET /search` - Search Gumtree listings with rich filters - `GET /search-by-url` - Run a search from a Gumtree search URL - `GET /search-suggestions` - Keyword autocomplete with categories - `GET /trending-searches` - Currently trending search terms - `GET /listing` - Full listing detail by ad ID - `GET /listing-by-url` - Listing detail from a listing URL - `GET /similar-listings` - Similar listings for an ad ID - `GET /locations-autocomplete` - Find location IDs for search - `GET /locations-nearest` - Reverse-geocode a coordinate to a location - `GET /countries` - ISO country list - `GET /categories` - Category tree, optionally a subtree - `GET /filters` - Available filters for a category - `GET /filter-options` - Selectable values for one attribute filter - `GET /seller` - Public seller profile - `GET /seller-listings` - A seller's active listings - `GET /seller-reviews` - A seller's reviews The Gumtree UK API provides structured access to one of the UK's largest classifieds marketplaces. Search listings across every category, retrieve complete ad details and seller data, and tap into category, location, and trend intelligence through clean JSON endpoints. ## What You Can Access Listing search covers the full Gumtree catalog - cars and vehicles, home and garden, electronics, jobs, services, pets, and general classifieds - with keyword, category, location, distance, price range, seller type, and per-category attribute filters. You can also resolve an existing Gumtree search URL into results, return keyword autocomplete suggestions with matching categories, and pull the terms currently trending on the platform. Listing endpoints return full ad detail by ID or directly from a listing URL, including description, price, media, attributes, and location, and `/similar-listings` surfaces comparable ads for recommendation features. Seller endpoints return public profiles, a seller's active listings, and their reviews, useful for lead qualification and marketplace trust analysis. Category and location intelligence includes the complete category tree, available filters per category with selectable values for each attribute, location autocomplete for search, and reverse geocoding from coordinates to a Gumtree location. ## Use Cases - Marketplace intelligence and competitive analysis - Price monitoring across UK second-hand goods and vehicles - Lead generation from listings and seller profiles - Classifieds aggregators and search products - Demand research via trending searches and category volumes - AI shopping assistants and recommendation engines ## Coverage Nationwide UK coverage across all Gumtree categories, from vehicles and home goods to jobs and services, with seller, category, and location detail. ## Related APIs For other classifieds marketplaces, see the [Njuškalo Croatia API](/library/njuskalo-api) or the [Yad2 Israel API](/library/yad2-api). For UK property data specifically, see the [Rightmove UK API](/library/rightmove-uk), or browse the full [API Library](/library). ## Further reading - [Classifieds API guide: Njuskalo and Gumtree marketplace data](/blog/classifieds-api-njuskalo-gumtree-marketplace-data) --- # Realtor.com Data API US property data from Realtor.com. Search homes for sale, rent, and sold, get full listing detail, valuations, agents, schools, mortgage rates, and market stats. - Page: https://happyendpoint.com/library/realtor-com-api - RapidAPI: https://rapidapi.com/happyendpoint/api/realtor-com-data-api - RapidAPI host: `realtor-com-data-api.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: realtor-com-data-api.p.rapidapi.com` and `x-api-key: ` - Tags: real-estate, listings, valuation, agents, schools, mortgage ## Features - For Sale, For Rent, and Sold Search - Off-Market and Public Records Search - Coordinate, Polygon, and Commute Search - Search by URL - Full Listing Details - Details by Address - Similar Homes and Comps - RealEstimate Property Valuation - Environmental and Climate Risk - New Construction Inventory - Agent Directory, Reviews, and Listings - Schools and School Districts - Live Mortgage and Lender Rates - Market Hotness and Geo Statistics - Neighborhood Guides and Map Boundaries ## Endpoints (37) - `GET /search` - Search US homes for sale, rent, or sold with rich filters and pagination - `GET /properties-for-sale` - Homes currently for sale, with the full filter surface - `GET /properties-for-rent` - Homes and apartments currently for rent, priced as monthly rent - `GET /properties-sold` - Recently sold homes, the comparable-sales dataset - `GET /search-by-coordinates` - Homes within a radius of a lat/lon point - `GET /search-by-polygon` - Homes inside a custom map polygon - `GET /search-by-commute` - Homes within a drive or walk time of a point - `GET /search-by-url` - Run a search from a Realtor.com search-results URL - `GET /property-search` - Search the full property universe, including off-market and sold records - `GET /records-by-owner` - Public-records property search by owner name - `GET /new-construction` - New-construction plans and ready-to-build builder inventory - `GET /locations-autocomplete` - Find location slug IDs and centroids to search by - `GET /property-details` - Full listing detail by property ID - `GET /property-details-by-url` - Full listing detail from a Realtor.com listing URL - `GET /property-details-by-address` - Full listing detail from a street address - `GET /similar-homes` - Comparable and similar homes for a property - `GET /property-environment` - Flood, wildfire, heat, wind, air, and noise risk for a property - `GET /property-valuation` - RealEstimate valuation with every AVM source, history, and forecast - `GET /agents-search` - Search the agent directory by ZIP or city with true match counts - `GET /agent-details` - Full agent profile with licence, brokerage, ratings, and listing stats - `GET /agent-reviews` - Client reviews for an agent with per-dimension ratings and replies - `GET /agent-recommendations` - Client recommendations for an agent - `GET /agent-feedback` - Reviews and recommendations merged into one sortable feed - `GET /agent-listings` - An agent's listings by status - for sale, rent, sold, or off-market - `GET /schools-search` - Search schools and districts by city, ZIP, county, or neighborhood - `GET /school` - A single school by ID - `GET /school-district` - A school district by ID with enrolment, rating, and school count - `GET /mortgage-rates` - Current average mortgage rates by loan type for a ZIP - `GET /mortgage-calculator` - Estimated monthly payment breakdown for given loan terms - `GET /mortgage-lender-rates` - Live rate table from named lenders for a ZIP, loan amount, and LTV - `GET /market-hotness` - Market hotness score and badge for a ZIP - `GET /geo-statistics` - Median list, rent, and sold price plus market stats for a geography - `GET /neighborhood-info` - Neighborhood guide statistics and for-sale count - `GET /market-feed` - Location market pulse - new listings, open houses, and price drops - `GET /commute-time` - Travel time from a property to a destination address - `GET /map-boundary` - GeoJSON boundary polygon for a ZIP, city, neighborhood, or county - `GET /enums` - All accepted filter values and response-field vocabularies The Realtor.com Data API provides structured access to US residential property data. Search homes for sale, for rent, and recently sold, retrieve complete listing detail and automated valuations, and pull agent, school, mortgage, and market intelligence through clean JSON endpoints. ## What You Can Access Search is the deepest part of the API. `/search` covers for-sale, for-rent, and sold homes with a filter surface of roughly 97 parameters - price, beds, baths, square footage, lot size, year built, property type, HOA fees, days on market, keywords, open houses, price reductions, foreclosure status, pet policy, and dozens more. Dedicated `/properties-for-sale`, `/properties-for-rent`, and `/properties-sold` endpoints expose the same surface scoped to one status, and `/property-search` widens the net to the full property universe including off-market and public records. Geographic search is available four ways: radius around a coordinate, a custom map polygon, a commute-time isochrone from a point, and a pasted Realtor.com search URL. `/locations-autocomplete` resolves free text to the location slug IDs and centroids those searches take, and `/map-boundary` returns the GeoJSON polygon for a ZIP, city, neighborhood, or county. Property detail is available by ID, by listing URL, or directly from a street address, with `/similar-homes` returning comparables and `/property-environment` returning flood, wildfire, heat, wind, air, and noise risk scores. `/property-valuation` returns the RealEstimate automated valuation for a property across every AVM source it carries, with historical values and a forward forecast. Agent endpoints cover the directory with true match counts, full profiles including licence, languages, specializations, and brokerage, plus reviews, recommendations, a merged feedback feed with verification flags, and an agent's listings by status. School coverage includes search by city, ZIP, county, or neighborhood, single school lookups, and district records with enrolment and ratings. Mortgage and market data round out the API: current average rates by loan type for a ZIP, a payment calculator, a live lender rate table, market hotness scores, neighborhood guides, geo statistics with median list, rent, and sold prices, and a market feed of new listings, open houses, and price drops. ## Use Cases - US property search portals and real estate marketplaces - Investment analysis and comparable sales research - Home valuation and equity estimation tools - Agent lead generation and brokerage intelligence - Mortgage and affordability calculators - School-aware relocation and neighborhood research products - Market analytics dashboards and price monitoring ## Coverage Nationwide US coverage across all 50 states, spanning for-sale, rental, sold, off-market, and new-construction inventory, plus agents, schools, school districts, mortgage rates, and neighborhood-level market statistics. ## Related APIs For US distressed and auction inventory, see the [Auction.com API](/library/auction-com-api). For other property markets, see the [Rightmove UK API](/library/rightmove-uk) or the [Idealista API](/library/idealista-api), browse our [Real Estate Data hub](/real-estate-data), or view the full [API Library](/library). ## Further reading - [Zillow API alternatives in 2026](/blog/zillow-api-alternatives-realtor-com-data) ## Disclaimer This API is an independent service built by HappyEndpoint. It is not affiliated with, endorsed, or sponsored by Realtor.com or Move, Inc. All data is retrieved from publicly available sources. --- # Vrbo API Vacation rental data from Vrbo. Search listings by destination, dates, or map area, plus property detail, amenities, photos, rates, availability, and reviews. - Page: https://happyendpoint.com/library/vrbo-api - RapidAPI: https://rapidapi.com/happyendpoint/api/vrbo2 - RapidAPI host: `vrbo2.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: vrbo2.p.rapidapi.com` and `x-api-key: ` - Tags: travel, vacation-rentals, listings, pricing, reviews ## Features - Destination Search with Dates and Guests - Coordinate and Map Bounds Search - Search by URL - Search Filter Discovery - Location Autocomplete - Neighborhood Lookup - Full Property Details - Amenities and Room Breakdown - Full Photo Gallery - Bookable Rates and Stay Totals - Day-by-Day Availability Calendar - Guest Reviews and AI Review Digest - Host Profiles and Host Listings - Cancellation and Refund Policies ## Endpoints (21) - `GET /search` - Search vacation rentals with dates, guests, price, and filters - `GET /search-by-coordinates` - Search rentals around a latitude/longitude point - `GET /search-by-bounds` - Search rentals inside a rectangular map area - `GET /search-by-url` - Run a search from a Vrbo search URL - `GET /search-filters` - Available filter groups for a destination - `GET /locations-autocomplete` - Find destinations and their region IDs to search by - `GET /neighborhoods` - Named neighborhoods in a destination with filterable IDs - `GET /property-details` - Full rental detail by property ID - `GET /property-details-by-url` - Rental detail from a listing URL - `GET /property-amenities` - The full amenities list for one rental - `GET /property-rooms` - Room-by-room breakdown of beds, bathrooms, and shared spaces - `GET /property-photos` - The full photo gallery for one rental, grouped by room - `GET /property-prices` - Bookable rate plans and stay total over given dates - `GET /property-availability` - Day-by-day availability and nightly prices for a rental - `GET /property-cancellation-policy` - The refund schedule for a rental over specific dates - `GET /property-policies` - House rules, check-in times, registration number, and safety info - `GET /property-location` - Location, nearby points of interest with drive times, and a map image - `GET /property-reviews` - Paginated guest reviews for a rental - `GET /property-reviews-summary` - Review scorecard plus an AI digest of recurring guest feedback - `GET /property-host` - Host profile with Premier Host status, scores, and languages - `GET /host-listings` - Other rentals in the destination run by the same host The Vrbo API provides structured access to one of the largest vacation rental marketplaces in the world. Search listings by destination, coordinates, or map area with real check-in and check-out dates, then pull complete property detail, live rates, availability calendars, reviews, and host data through clean JSON endpoints. ## What You Can Access Search accepts a destination region ID, a coordinate with a radius, a rectangular map bounding box, or a pasted Vrbo search URL, combined with stay dates, guest and pet counts, price ranges, bedroom and bathroom minimums, property types, and amenity filters. `/locations-autocomplete` resolves free text to destinations and their region IDs, `/neighborhoods` returns the named neighborhoods you can narrow a search to, and `/search-filters` returns the filter groups available for a given destination. Property endpoints go well beyond a single detail call. Alongside `/property-details` (by ID or by URL) you get the complete amenities list, a room-by-room breakdown of beds and bathrooms, the full photo gallery grouped by room, and location data with nearby points of interest and drive times. Pricing and availability are first-class. `/property-prices` returns bookable rate plans and the total for a specific stay, `/property-availability` returns a day-by-day calendar with nightly prices, and `/property-cancellation-policy` returns the refund schedule for those exact dates. This is what makes the API usable for rate benchmarking and revenue analysis rather than just listing display. Trust and host data cover paginated guest reviews, a review scorecard with an AI digest of what guests repeatedly mention, the host profile behind a listing including Premier Host status, response scores, and languages, and the host's other listings in the same destination. ## Use Cases - Vacation rental metasearch and travel comparison products - Short-term rental rate benchmarking and revenue management - Occupancy and availability analytics for a market - Property management and host competitor intelligence - Destination market research and investment analysis - AI travel assistants that need structured rental inventory ## Coverage Global Vrbo inventory across destinations worldwide, spanning whole homes, condos, cabins, and villas, with rates, availability, amenities, photos, policies, reviews, and host detail for each listing. ## Related APIs For hotel, flight, and car rental pricing, see the [Priceline Pro API](/library/priceline-pro), browse our [Travel Data hub](/travel-data), or view the full [API Library](/library). ## Further reading - [No public Airbnb API: getting short-term rental data](/blog/airbnb-api-alternative-vrbo-rental-data) ## Disclaimer This API is an independent service built by HappyEndpoint. It is not affiliated with, endorsed, or sponsored by Vrbo or Expedia Group. All data is retrieved from publicly available sources. --- # 28Hse Hong Kong Property API Hong Kong property data from 28Hse. Search listings for sale and rent, estates, and new developments, plus transactions, agencies, school nets, and mortgages. - Page: https://happyendpoint.com/library/28hse-api - RapidAPI: https://rapidapi.com/happyendpoint/api/28hse-property-api - RapidAPI host: `28hse-property-api.p.rapidapi.com` - MCP: `https://mcp.rapidapi.com` with headers `x-api-host: 28hse-property-api.p.rapidapi.com` and `x-api-key: ` - Tags: real-estate, listings, transactions, hong-kong, mortgage ## Features - Property Search for Sale and Rent - Residential Estate Search - New Development Search - Listing Details by ID or URL - Sale and Lease Transaction Records - Location Autocomplete - Property Filter Discovery - Agency Directory - School Net Directory - Serviced Apartment Directory - Bank Mortgage Plans - Property Market News ## Endpoints (13) - `GET /property-search` - Search listings for sale or rent by district, estate, price, area, and type - `GET /estate-search` - Search residential estates with price, volume, and rental-yield stats - `GET /new-property-search` - Search new-development pre-sale and first-hand projects - `GET /property-details` - Full detail for a single property listing by ad ID - `GET /property-details-by-url` - Full property listing detail from a listing URL - `GET /transactions` - Recent sale and lease transaction records, optionally by estate - `GET /location-autocomplete` - Autocomplete estates and districts to discover search IDs - `GET /property-filters` - Available property type, sort, and price-range options - `GET /agent-search` - Agency directory with per-district listing counts - `GET /school-net-search` - Schools by school net, district, type, and gender or religion - `GET /service-apartment-search` - Serviced apartments and hotels with room types and price ranges - `GET /mortgage-plans` - Current bank mortgage plans with rate, cash rebate, and penalty period - `GET /news-search` - Property-market news and video articles The 28Hse Hong Kong Property API provides structured access to one of Hong Kong's largest property portals. Search listings for sale and rent, browse residential estates and new developments, and pull transaction records, agency and school data, and current mortgage plans through clean JSON endpoints. ## What You Can Access Property search covers listings for sale and for rent across Hong Kong Island, Kowloon, and the New Territories, filterable by district, estate, price range, floor area, and property type. `/property-filters` returns the valid property type, sort, and price-range options for a search, and `/location-autocomplete` is the front door for discovery: type an estate or district name and get back the IDs the search endpoints expect. Estate search is the layer above individual listings. `/estate-search` returns residential estates and buildings with price, transaction volume, and rental-yield statistics, which is the view an investor actually wants when comparing buildings rather than units. `/new-property-search` covers pre-sale and first-hand development projects. Listing detail is available by ad ID or directly from a 28Hse listing URL, and `/transactions` returns recent registered sale and lease records, optionally scoped to a single estate. Combined with estate yield stats, that gives you real transacted prices rather than asking prices alone. Directory endpoints cover agency companies with per-district listing counts, schools organised by school net with type and gender or religion attributes, and serviced apartments and hotels with room types and price ranges. Finance and market context come from `/mortgage-plans`, which returns current bank mortgage offers with rate, cash rebate, and penalty period, and `/news-search` for property-market news and video articles. ## Use Cases - Hong Kong property search portals and proptech products - Investment analysis using estate-level yields and transaction comps - Price monitoring across districts and named estates - Agency and brokerage competitive intelligence - School-net-aware relocation and family housing tools - Mortgage comparison and affordability calculators ## Coverage Hong Kong-wide coverage across Hong Kong Island, Kowloon, and the New Territories, spanning for-sale and rental listings, residential estates, new developments, transaction records, agencies, school nets, serviced apartments, and bank mortgage plans. ## Related APIs For other Asian property markets, see the [SUUMO Japan Real Estate API](/library/suumo-api) or the [99.co Singapore API](/library/99co-api), browse our [Real Estate Data hub](/real-estate-data), or view the full [API Library](/library). ## Further reading - [28Hse API: Hong Kong listings, estates and transactions](/blog/28hse-api-hong-kong-property-data) ## Disclaimer This API is an independent service built by HappyEndpoint. It is not affiliated with, endorsed, or sponsored by 28Hse. All data is retrieved from publicly available sources. --- # Datasets (14) # Bayut UAE Real Estate Agents Database 19,892 active UAE real estate agents from Bayut.com with contact details, listing activity, trust signals, and agency data. 39 columns. Scraped May 2026. - Page: https://happyendpoint.com/datasets/bayut-agents-2026 - Records: 19,892 agents - Format: Excel (XLSX) - Price: Contact Us ## Fields and features - Full name in English and Arabic - Email, phone, cell, and WhatsApp numbers (direct and proxy) - Contact availability flags (email, call, WhatsApp) - Active listing counts (sale, rent, daily rental) - TruBroker status (9,079 agents) - Quality Lister status (11,222 agents) - Highly Responsive status (10,523 agents) - Review count and average star rating - TruCheck and verified listing counts - Agency name, phone, mobile, and RERA license number - Agency logo URL - Specialisations and service areas per agent - Languages spoken - 39 columns per agent, one row per record Every active real estate agent currently listed on Bayut.com is in this file. 19,892 records across 4,247 agencies and all major UAE emirates - Dubai, Abu Dhabi, and Sharjah. ## What you get Each row is a single agent. The 39 columns cover three areas: identity and contact, listing activity, and trust signals. **Contact data** is the primary reason most buyers use this dataset. 19,892 records include email. 15,656 include a direct phone number. 19,293 include a WhatsApp number. Proxy numbers (platform-managed) are included alongside direct numbers, so you have both channels available. Contact availability flags tell you whether each agent has enabled email, call, and WhatsApp contact on their profile. **Listing activity** shows each agent's total active listing count broken down by sale, rent, and daily rental. The primary category (residential or commercial) and purpose (for sale or for rent) are included, along with the number of distinct locations where each agent has active listings. **Trust and quality signals** come directly from Bayut's own verification system. TruBroker status, Quality Lister designation, Highly Responsive flag, TruCheck verified listing count, and review count with average star rating are all included per agent. **Agency data** links each agent to their employer. Agency name, phone, mobile, RERA license number, and logo URL are included in every record where the agent is affiliated with an agency. ## Column list `profile_url` `name` `name_l1` `email` `phone` `cell` `whatsapp` `proxy_phone` `proxy_mobile` `proxy_whatsapp` `activeInEmirate` `service_areas` `specialities` `user_langs` `about_user` `sale_count` `rent_count` `daily_rent_count` `adsCount` `trucheck_count` `check_count` `reviewCount` `avgStarRating` `isTruBroker` `isQualityLister` `isHighlyResponsive` `hasBadges` `contact_email` `contact_call` `contact_whatsapp` `best_category` `best_purpose` `locations_with_ads_count` `user_image` `agency_name` `agency_phone` `agency_mobile` `agency_rera` `agency_logo_url` ## Who uses this **PropTech and CRM platforms** use the dataset to pre-populate agent directories, enrich lead databases, and map agent coverage across the UAE by emirate and specialisation. **Mortgage brokers and financial services** use it to identify high-volume agents to target for referral partnership pipelines. **Real estate recruiters** filter by specialisation, emirate, listing activity, and trust score to find top-performing agents across rival agencies. **Market research firms** analyse agent distribution, agency market share, and activity levels across UAE emirates. **Real estate agencies** use it for competitive intelligence - agent counts, specialisations, and trust scores across other firms in their target areas. ## Dataset specs | Field | Value | |---|---| | Total records | 19,892 | | Agencies covered | 4,247 | | Emirates | Dubai, Abu Dhabi, Sharjah | | Columns | 39 | | Format | Excel (XLSX) | | File size | 44 MB | | Scraped | May 2026 | ## Want the change, not the snapshot? This dataset is a point-in-time file. If you need the movement tracked daily - price drops, delistings, agents going to zero - see the [UAE data feeds](/data-feeds), updated every day. ## Want the change, not the snapshot? This dataset is a point-in-time file. If you need the movement tracked daily - price drops, delistings, agents going to zero - see the [UAE data feeds](/data-feeds), updated every day. --- # IKEA US Complete Product Catalog 10,564 IKEA US products across 933 categories with pricing, ratings, images, badge data, and full category paths. 31 columns. Scraped April 2026. - Page: https://happyendpoint.com/datasets/ikea-products-us - Records: 10,564 products - Format: CSV - Price: $249 ## Fields and features - Product name, type, item number, and dimensions - USD price with discount flag and sale tags - Star rating (0 to 5) and review count - Badge data (Best Seller, New, Last Chance flags) - Online sellable flag - Primary product image URL and alt text - Contextual lifestyle image URL and alt text - Color count, color names, and variant count - Category ID, name, and full path - Direct URL to the live IKEA product page - 31 columns per product, one row per record 10,564 IKEA US products across 933 categories - scraped directly from IKEA's US catalog in April 2026. Every row is a product. Open the CSV and start working. ## What you get 31 fields per product covering identity, pricing, social proof, merchandising signals, images, and categorisation. **Product identity** includes name, type description, item number (US and global variants), and dimensions where provided. Color and variant data covers the number of available colors, color names, and total variant count - useful for building configurators or variant-aware recommendation logic. **Pricing** is captured as a numeric USD value with a boolean discount flag and sale tag text where applicable. Prices are stored as numbers, not strings - no parsing required. **Social proof**: star rating on a 0 to 5 scale and total review count per product. **Merchandising signals**: badge type (Best Seller, New, etc.) and badge label text, a last-chance flag for products being discontinued, and an online sellable flag indicating availability for online purchase. **Images**: direct CDN URLs for both the primary product image and the contextual lifestyle/room-setting image, with alt text for each. **Category**: category ID, category name, and full category path (for example, Storage and organization > Shelving furniture > Bookshelves and bookcases). 933 unique categories are covered end-to-end. **Product URL**: direct link to the live IKEA US product page for each record. ## Column list `productId` `itemNo` `itemNoGlobal` `name` `typeName` `dimensions` `validDesignText` `price` `currencyCode` `discount` `ratingValue` `ratingCount` `badge` `badgeType` `pipUrl` `mainImageUrl` `mainImageAlt` `contextualImageUrl` `contextualImageAlt` `colorCount` `colorsText` `variantCount` `quickFactsText` `businessArea` `productArea` `productRangeArea` `onlineSellable` `lastChance` `categoryId` `categoryName` `categoryPath` ## Who uses this **E-commerce and affiliate marketers** building furniture comparison sites, price tracking tools, or affiliate stores that feature IKEA products. **Interior design apps** that need a structured product catalog with images, dimensions, and categories to power product recommendations or room-planning features. **Price tracking and market research teams** monitoring IKEA's US catalog for assortment changes, new launches, and pricing movements. **Developers and data engineers** building recommendation engines, furniture classification models, or product search indexes. **Dropshippers and resellers** researching IKEA's full US product range across all categories. ## Dataset specs | Field | Value | |---|---| | Total products | 10,564 | | Categories | 933 | | Columns per row | 31 | | Format | CSV (UTF-8) | | File size | 8 MB | | Market | IKEA United States | | Scraped | April 2026 | | Price | USD 249, one-time payment | --- # Sephora US Product Data 8,000+ Sephora US products with brand data, USD pricing, star ratings, review counts, category paths, product page URLs, and image URLs. CSV download. - Page: https://happyendpoint.com/datasets/sephora-products-us - Records: 8,000+ products - Format: CSV - Price: $99 ## Fields and features - Unique Sephora product and SKU identifiers - Brand name (e.g. Fenty Beauty, Dior, Rare Beauty) - Product display name as listed on Sephora - USD list price - Average customer star rating - Total customer review count - Direct product page URL - Primary product image URL - Full category hierarchy path - 10 columns per product, one row per SKU 8,000+ Sephora US product records in a single CSV, scraped from Sephora.com in 2026. Every row is a product SKU. Every column is immediately useful. ## What you get 10 fields per product, flat structure, no nested data. Open the file and start working - no cleanup or post-processing required. **Identity**: each record has a unique Sephora product ID and SKU-level ID. Brand name and product display name are included as text fields, exactly as they appear on Sephora.com. **Pricing**: USD list price as a numeric value, ready for arithmetic without parsing. **Social proof**: average customer star rating and total review count per product. These two fields together give a reliable signal of popularity and product quality across Sephora's catalog. **Product URL**: direct link to the product page on Sephora.com for every record. **Image URL**: the main product image URL for building visual displays, product cards, or training image models. **Category path**: the full category hierarchy for each product - for example, Skincare > Moisturizers > Face Moisturizers. Use this to filter by category, build category-level analytics, or train classification models. ## Who uses this **E-commerce sellers and affiliate marketers** tracking Sephora's US assortment and pricing for comparison or affiliate link building. **Beauty market researchers** analysing brand distribution, price positioning, and rating patterns across Sephora's catalog. **Data analysts and developers** building beauty product recommendation engines, price monitors, or category-level trend dashboards. **Pricing intelligence teams** monitoring Sephora's list prices across brands and categories. ## Dataset specs | Field | Value | |---|---| | Total products | 8,000+ | | Columns per row | 10 | | Format | CSV | | File size | 10 MB | | Market | United States | | Marketplace | Sephora US | | Price | USD 99, one-time payment | --- # PropertyFinder UAE Real Estate Agents Dataset 19,994 active UAE real estate agents from PropertyFinder with 51 fields - contact details, performance metrics, transaction history, and agency data. - Page: https://happyendpoint.com/datasets/propertyfinder-agents-2026 - Records: 19,994 agents - Format: Excel (XLSX) - Price: $349 ## Fields and features - Full name, profile URL, email, phone, and WhatsApp number - BRN license number and LinkedIn URL - Platform ranking, average rating, and full rating distribution (1 to 5 stars) - Median listing quality score - Active listings by type (residential sale, residential rent, commercial sale, commercial rent) - Transaction count, claimed deal volume in AED, and average sale and rent prices - Average WhatsApp response time in minutes - Superagent and verified status flags - Nationality code and years of experience - Languages spoken (pipe-separated list) - Agency name, slug, address, city, and logo URL - 51 columns per agent, one row per record All 19,994 active agents on PropertyFinder UAE - not a sample, not a filtered subset. Every row is an agent. Every column is useful. ## What you get 51 fields per agent, structured for immediate use in CRM import, scoring models, or market analysis. No cleanup required. **Contact and identity** covers full name, direct profile URL, email, phone, WhatsApp number, LinkedIn URL, profile photo URL, and BRN license number. Nationality code, years of experience, position title, and bio are included where available. **Performance metrics** go further than most agent directories. Platform ranking, average rating, and the full rating distribution across all five star levels are included per agent. Median listing quality score is also provided - a PropertyFinder-specific signal that reflects how completely an agent fills out their listings. **Active listings** are broken down by four types: residential sale, residential rent, commercial sale, and commercial rent. Total active property count is also included. **Transaction history** is the most distinctive part of this dataset. Claimed deal counts (sale and rent), total deal volume in AED, and average sale and rent prices are included per agent. This gives a financial dimension that is rare in agent data - enough to build a meaningful scoring model based on historical performance. **Response behavior**: average WhatsApp response time in minutes, where available. **Agency data** links each agent to their agency with agency ID, name, slug, full address, city, and logo URL. ## Column list `id` `name` `profile_url` `email` `phone` `whatsapp_phone` `user_id` `position` `bio` `license_number` `brn_number` `nationality_code` `linkedin_url` `experience_since_year` `is_superagent` `is_verified` `ranking` `average_rating` `review_count` `rating_1_count` `rating_2_count` `rating_3_count` `rating_4_count` `rating_5_count` `median_listing_quality` `total_properties` `listings_residential_sale` `listings_residential_rent` `listings_commercial_sale` `listings_commercial_rent` `transactions_count` `avg_whatsapp_response_mins` `claimed_sale_count` `claimed_rent_count` `claimed_deal_volume_aed` `claimed_sale_total_aed` `claimed_rent_total_aed` `claimed_sale_avg_aed` `claimed_rent_avg_aed` `photo_url` `agency_id` `agency_name` `agency_slug` `agency_address` `agency_city` `agency_logo_url` `languages` `languages_count` `top_location_ids` `top_locations_count` ## Who uses this **PropTech and CRM platforms** building agent directories, lead routing systems, or agent scoring models for the UAE market. **Real estate investment firms** doing due diligence on which agents are most active in specific areas or property types. **Marketing and outreach agencies** targeting UAE real estate professionals for B2B campaigns - email, phone, and WhatsApp numbers are included. **Recruitment platforms and HR teams** identifying experienced agents or high-performers to recruit, filtered by ranking, transaction volume, or language profile. **Market research and analytics firms** studying agent distribution, agency size, language coverage, or performance benchmarks across the UAE. ## Dataset specs | Field | Value | |---|---| | Total agents | 19,994 | | Columns per row | 51 | | Format | Excel (XLSX) | | File size | 38 MB | | Market | UAE (United Arab Emirates) | | Scraped | May 2026 | | Price | USD 349, one-time payment | ## Want the change, not the snapshot? This dataset is a point-in-time file. If you need the movement tracked daily - price drops, delistings, agents going to zero - see the [UAE data feeds](/data-feeds), updated every day. ## Want the change, not the snapshot? This dataset is a point-in-time file. If you need the movement tracked daily - price drops, delistings, agents going to zero - see the [UAE data feeds](/data-feeds), updated every day. --- # Sephora Customer Reviews Dataset 500,000+ verified customer reviews from Sephora US with star ratings, skin type, review text, and helpfulness votes - ideal for NLP and sentiment analysis. - Page: https://happyendpoint.com/datasets/sephora-reviews-dataset - Records: 500,000+ reviews - Format: JSON / CSV - Price: Contact Us ## Fields and features - Full review text with title and body - Star rating (1-5) per review - Reviewer skin type, tone, and age range - Helpfulness votes (found helpful / not helpful) - Verified purchase flag - Product ID and brand cross-reference - Review date for time-series analysis - Incentivized review disclosure flag The Sephora Customer Reviews Dataset aggregates over 500,000 individual product reviews from Sephora.com. Each review includes the full text, a star rating, and structured metadata about the reviewer - skin type, skin tone, age range, and eye color - making it one of the richest beauty review datasets available for NLP research and consumer insights work. ## What's included Every record represents a single review tied to a specific product SKU. The review text field contains both the short title and the full body, preserved exactly as submitted. Ratings run from 1 to 5 stars. Helpfulness signals capture how many other shoppers marked the review as helpful or not helpful, which makes it straightforward to weight or filter by review quality. Reviewer attributes - skin type (dry, oily, combination, normal), skin tone (fair, light, medium, tan, deep), and age range (18-24, 25-34, 35-44, 45-54, 55+) - are self-reported by the reviewer at the time of posting. These fields are valuable for building personalization models that surface products best suited to a user's profile. The verified purchase flag distinguishes organic reviews from incentivized or seeded ones. An incentivized disclosure flag captures the subset of reviews where Sephora has flagged the reviewer received the product for free. ## Ideal use cases Sentiment analysis and aspect-based opinion mining teams use this dataset to train models that extract fine-grained opinions about product attributes (texture, scent, longevity, packaging). Recommendation systems use the reviewer profile metadata to surface products for specific skin types. Academic researchers studying online review behavior use the helpfulness vote and incentivization fields for econometric modeling. ## Delivery Delivered as CSV or line-delimited JSON. Snapshots are produced monthly. Cross-reference keys align with the Sephora US Full Product Catalog dataset so the two can be joined on product ID. --- # PropertyFinder UAE Real Estate Transactions Dataset 128,000+ UAE real estate transactions with property type, bedroom count, area in sqft, transaction price, price per sqft, location data, and contract dates. - Page: https://happyendpoint.com/datasets/propertyfinder-transactions-data - Records: 128,000+ transactions - Format: CSV - Price: $249 ## Fields and features - Property type and offering type (sale or rent) - Number of bedrooms - Property size in square feet - Transaction price and price per square foot - Location details (slug, name, and high-level area) - Transaction status - Transaction date and contract date - Coverage across Dubai, Abu Dhabi, Sharjah, and other UAE emirates - Both sale and rental transactions included - Delivered as CSV, also available as SQLite or JSON on request 128,000+ UAE real estate transactions scraped from PropertyFinder - covering both for-sale and rental properties across all major UAE emirates. Every row is a transaction. ## What you get Each record contains the core fields needed for property market analysis: property type, offering type (sale or rent), bedroom count, size in square feet, transaction price, and price per square foot. Location is captured at three levels - slug, location name, and high-level area - making it straightforward to aggregate by neighbourhood, district, or emirate. Transaction status, transaction date, and contract date are included so you can filter by time period, identify recent transactions, or model time-series price trends. ## Use cases **Market analysis**: identify pricing trends across locations, property types, and time periods. Track how price per square foot has shifted in specific communities. **Investment research**: discover undervalued areas, calculate indicative rental yields, and identify high-growth zones based on historical transaction volume and price movement. **Machine learning and AI models**: build property price prediction models, rental estimators, or valuation tools using historical transaction data as training signal. **Business intelligence dashboards**: build internal or client-facing dashboards covering UAE property market dynamics - price bands, transaction volume, and location-level heat maps. **Competitor and market monitoring**: track shifts in supply, demand, and pricing dynamics across the UAE real estate market over time. ## Coverage - Multiple cities and regions across the United Arab Emirates - Both residential and commercial property categories - Both sale and rental transactions ## Dataset specs | Field | Value | |---|---| | Total records | 128,000+ | | Format | CSV (also available as SQLite or JSON) | | File size | 23 MB | | Market | UAE (United Arab Emirates) | | Price | USD 249, one-time payment | ## Custom format or questions Contact happyendpointhq@gmail.com for SQLite or JSON format requests, or for questions about the data. ## Want the change, not the snapshot? This dataset is a point-in-time file. If you need the movement tracked daily - price drops, delistings, agents going to zero - see the [UAE data feeds](/data-feeds), updated every day. ## Want the change, not the snapshot? This dataset is a point-in-time file. If you need the movement tracked daily - price drops, delistings, agents going to zero - see the [UAE data feeds](/data-feeds), updated every day. --- # Rightmove Sold Prices Dataset Historical UK property sold prices for market analysis. - Page: https://happyendpoint.com/datasets/rightmove-sold - Records: 5M+ records - Format: JSON / CSV - Price: Contact Us ## Fields and features - Sold prices - Historical data - Market trends - Monthly updates Historical UK property sold prices for market analysis. --- # Sephora US Products Free Sample Free sample of Sephora US product data with 10 fields per record - brand, price, rating, reviews, product URL, image URL, and category path. Free CSV download. - Page: https://happyendpoint.com/datasets/sephora-bestsellers-free - Records: Sample - Format: CSV - Price: Free ## Fields and features - Unique Sephora product and SKU identifiers - Brand name (e.g. Fenty Beauty, Dior, Rare Beauty) - Product display name as listed on Sephora - USD list price - Average customer star rating - Total customer review count - Direct product page URL - Primary product image URL - Full category hierarchy path - Same 10-column schema as the full paid dataset A free slice of Sephora US product data - same schema as the full 8,000+ product dataset. Download it, run your analysis, confirm the data quality, then buy the full version if it fits your use case. ## What you get The same 10 columns as the full paid dataset: `productId`, `skuId`, `brandName`, `displayName`, `listPrice`, `rating`, `reviews`, `targetUrl`, `heroImage`, `categoryPath`. Every field is identical between this free sample and the paid product. Any pipeline, model, or tool you build against this sample will work without modification when you upgrade to the full dataset. ## Why it's free Buying data without seeing it first is a bad deal. This sample exists so you can inspect the field names, verify the data types, check for the brands and categories you care about, and confirm the schema fits your system - before paying anything. ## Upgrade to the full dataset The full Sephora US Product Data (8,000+ products, $99) is available at the link above. It covers Sephora's complete US catalog with the same clean, flat structure as this sample. --- # Ikea Catalog Sample Sample Ikea products across categories. Includes images and dimensions. - Page: https://happyendpoint.com/datasets/ikea-catalog-sample - Records: 500 products - Format: JSON / CSV - Price: Free ## Fields and features - Multiple categories - Image URLs - Dimensions Sample Ikea products across categories. Includes images and dimensions. --- # Sephora Skincare Sample Free sample of 1,000 Sephora skincare products with ingredients, skin type compatibility, and customer ratings. Perfect for testing ML pipelines. - Page: https://happyendpoint.com/datasets/sephora-skincare-sample - Records: 1,000 products - Format: JSON / CSV - Price: Free ## Fields and features - 1,000 skincare SKUs across moisturizers, serums, SPF, and cleansers - Full ingredient lists as parsed arrays - Skin type compatibility tags (dry, oily, combination, sensitive) - Concern tags (anti-aging, brightening, acne, hydration) - Star ratings and review counts - Brand and sub-brand fields - Price and size/volume information The Sephora Skincare Sample is a curated free dataset of 1,000 skincare products drawn from Sephora's full catalog. It covers the four most-searched skincare subcategories - moisturizers, serums, SPF products, and cleansers - and is designed to be immediately useful for machine learning experiments, ingredient analysis tools, and skincare recommendation prototypes. ## What's included Each record is a single skincare product SKU. Ingredient data is provided as a parsed array of INCI names rather than a raw string, so you can build ingredient overlap detectors or clean/vegan filters without writing your own parser. Skin type compatibility and concern tags are taken directly from Sephora's structured product metadata - these reflect how Sephora categorizes the product, not inferred values. Tags include skin types (dry, oily, combination, normal, sensitive) and skin concerns (anti-aging, brightening, dark spots, acne, redness, hydration). Price is captured as the retail price at snapshot time. Where volume or size information is present (e.g. 30ml, 1 fl oz), it is included in a separate field so you can calculate price-per-ml comparisons across products. ## Why it's free Ingredient and skincare compatibility data is one of the most-requested dataset types among our customers. This free sample lets you validate that the schema fits your use case before purchasing the full skincare slice or the complete Sephora US catalog. ## Ideal use cases Building an ingredient checker or "is this clean?" classifier. Prototyping a skin type recommendation engine. Academic research on cosmetic ingredient trends. Price comparison tools for the skincare vertical. --- # Tesco UK Products Dataset Complete catalog of Tesco UK products with pricing, nutrition data, and offers. - Page: https://happyendpoint.com/datasets/tesco-products-uk - Records: 500K+ products - Format: JSON / CSV - Price: Contact Us - Free sample available: Tesco UK Products Sample (1,000 products) ## Fields and features - Full catalog - Nutrition data - Price history - Weekly updates Complete catalog of Tesco UK products with pricing, nutrition data, and offers. --- # Rightmove Sales Sample Sample UK property sales listings from London area. Great for prototyping. - Page: https://happyendpoint.com/datasets/rightmove-sales-sample - Records: 5,000 properties - Format: JSON / CSV - Price: Free ## Fields and features - London area - Full schema - Property details Sample UK property sales listings from London area. Great for prototyping. --- # Rightmove Rentals Sample Sample UK rental listings for testing rental data pipelines. - Page: https://happyendpoint.com/datasets/rightmove-rentals-sample - Records: 3,000 properties - Format: JSON / CSV - Price: Free ## Fields and features - Rental listings - Full schema - Agent info Sample UK rental listings for testing rental data pipelines. --- # Priceline Hotels Sample Sample hotel data from major US cities for testing travel apps. - Page: https://happyendpoint.com/datasets/priceline-hotels-sample - Records: 2,000 hotels - Format: JSON / CSV - Price: Free ## Fields and features - Major cities - Pricing data - Amenities Sample hotel data from major US cities for testing travel apps. --- # Data feeds (2) # PropertyFinder Dubai Agent Movement Feed 6,940 agents are under 7 listings today. 130 of them change every 24 hours. Daily-tracked feed on every agent on PropertyFinder Dubai - listing counts, ranking, deal volume, phone, WhatsApp and email, with day-by-day movement. - Page: https://happyendpoint.com/data-feeds/propertyfinder-dubai-agent-movement - Coverage: PropertyFinder Dubai (UAE Real Estate) - Update cadence: Daily - Delivery: Google Sheet, updated daily - Source: PropertyFinder public agent profiles ## At a glance - 25,115 agents tracked - Daily update cadence - 100% have phone + email - 91% have WhatsApp ## What it tracks ### Movement in a single day What changed between two daily scrapes - **130** Crossed below 7 listings - Entered your target segment in one day. A static list never catches these. - **72** Dropped to zero listings - The strongest sign an agent is leaving, or has left, their agency. - **2,188** Lost listings - Losing inventory, often the first sign of an unhappy agent. - **3,416** Fell in ranking - Performance shifts across the board every day. - **5,035** Changed listing count - 25% of active agents moved in 24 hours. - **59** New agents appeared - Fresh licences and new-to-market agents. - **69** Left the platform - Profiles that went dark since yesterday. - **6,940** Under 7 listings now - The live size of the low-inventory segment. ### Movement over the quarter The churn a one-time scrape can never show you - **3,966** Left PropertyFinder - 16% of the agent base turned over in ten weeks. - **4,277** New agents joined - A fresh recruitment pipeline, tracked from day one. - **8,016** Grew their listings - Agents building momentum you can benchmark. - **1,441** Declined over 50% - Sharp drops that flag agents at risk of moving. - **1,168** Crossed below 7 - Entered the low-inventory segment during the period. - **304** Lost superagent status - Standing changes worth watching. ## A snapshot is wrong within 24 hours Anyone can scrape a list of agents once. The problem is that **5,035 agents change their listing count every single day**, 130 cross below seven, and dozens go dark. By the time a one-time export reaches you, it is already describing a market that has moved on. Because this feed is captured daily and kept as history, it does not just tell you the state today. It tells you the **direction**: who is slowing down, who just went to zero, who is brand new, who is climbing. That direction is the difference between a phone list and a reason to call. ## Sample output Columns: Agent | Agency | Listings | 7-day change | Phone / WhatsApp | Signal Names and numbers are masked in this preview. Live delivery includes full agent name, agency, phone, WhatsApp, email, ranking, ratings, and deal-volume history, in a Google Sheet updated daily. --- # PropertyFinder Dubai Listings and Price-Change Feed 42,932 Dubai listings cut their asking price. We caught every one. Daily-tracked feed across 800,000 Dubai listings recording every price drop, delisting and day on market, the day it happens. Motivated-seller signals. - Page: https://happyendpoint.com/data-feeds/propertyfinder-dubai-price-changes - Coverage: PropertyFinder Dubai (UAE Real Estate) - Update cadence: Daily - Delivery: Google Sheet, updated daily - Source: PropertyFinder public listings ## At a glance - 801,459 listings tracked - 13.2M price points - 50 avg days on market - Daily update cadence ## What it tracks ### Movement in one week How much the market moves in a single week - **5,898** Price drops - Asking prices cut by an average of 7.0% in a single week. - **64,376** New listings - Roughly 9,200 new listings entering the market each day. - **63,594** Delisted or sold - Listings that left the market, tracked the day they vanished. - **395,006** Live listings - Active inventory captured in the latest snapshot. - **1,063** Price increases - Where sellers pushed asking prices up. - **22,446** Premium listings - The paid-promotion segment, tracked separately. ### Price behaviour over the period Which listings moved, and by how much - **42,932** Listings that cut price - Average reduction of 7.8%, with some cut by more than half. - **7,311** Listings that raised price - Upward repricing across the market. - **50** Avg days on market - Measured from listed date to last seen, per property. ## The price today tells you nothing. The change does. A one-time listings export gives you a price. It cannot tell you that the price was **cut 12% last Tuesday**, that the property has been sitting for 90 days, or that it quietly delisted this morning. Those are the moments that matter to a buyer, an investor, or a valuation model. Because this feed is captured daily and kept as history, every listing carries its own price timeline, its days on market, and its exit. That turns a directory into a **signal source**: motivated sellers, stale inventory, and real absorption, area by area. ## Sample output Columns: Community | Type | Beds | Prev price | New price | Change | Days live | Event Values shown are illustrative. Live delivery includes property reference, full location, price timeline, size, days on market, agent and broker contact, and availability status. --- # Articles (28) # Classifieds API guide: Njuskalo and Gumtree data Classifieds data is messy in ways retail data is not. How the Njuskalo and Gumtree APIs handle categories, sellers and attributes, and what to build with them. - Page: https://happyendpoint.com/blog/classifieds-api-njuskalo-gumtree-marketplace-data - Published: 2026-08-29 - Tags: njuskalo, gumtree, classifieds, marketplace, croatia, uk Classifieds data is harder than retail data, and the reason is that there is no catalog. A retailer has SKUs. Every listing maps to a known product with a known description. A classifieds site has whatever a stranger typed into a form. The same car appears as "VW Golf 7 2.0 TDI", "golf mk7 diesel" and "Volkswagen Golf, 2019, excellent condition". There is no identifier tying them together, and half the useful information is in free text. This guide covers how the [Njuškalo Croatia API](/library/njuskalo-api) and the [Gumtree UK API](/library/gumtree-api) model that problem. ## Category trees do the work On a classifieds site the category is the schema. A listing in "Cars" has mileage, year, fuel type and transmission. A listing in "Property" has rooms and floor area. A listing in "Furniture" has neither. Attributes are defined per category, so you cannot write one parser and be done. Both APIs expose this explicitly, which is what makes them workable. **Njuškalo** gives you `/category-navigation` for the tree, `/category-detail` for one node, and `/filter-options` for the selectable values on a category's attribute filters. Plus `/recommended-categories` and `/trending-categories`, which tell you where activity is concentrated right now. **Gumtree** gives you `/categories` for the tree or a subtree, `/filters` for the filters available on a category, and `/filter-options` for the values of a single attribute filter. The workflow is the same on both: walk the tree, pull the filter definitions for the categories you care about, then build your extraction per category. Trying to search first and infer structure later is the mistake. ## Search, and knowing what you missed **Njuškalo** has a genuinely useful pair. `/search` returns results; **`/search-count`** returns just the count. That second one solves the coverage problem. Classifieds search endpoints cap results, so "every car listing in Croatia" is not one query. Calling `/search-count` first tells you whether your filter combination is under the cap, and if not, you split it by price band or region and recurse. Without a count endpoint you are guessing, and you find out you were wrong when your dataset is quietly 60% complete. `/search-by-category` scopes to a branch, `/latest` returns the newest listings, and `/parse-url` turns a Njuškalo URL into structured query parameters - useful when someone hands you a link rather than a spec. **Gumtree** covers `/search` and `/search-by-url`, plus two demand-side endpoints: `/search-suggestions` for keyword autocomplete with matching categories, and **`/trending-searches`** for what people are currently looking for. Trending searches are a demand signal you cannot derive from listings, which are supply. Together they tell you where demand is outrunning inventory, which is the interesting part. ## Sellers, and why they matter Both APIs expose seller data, and on a classifieds marketplace this is often where the commercial value sits. Njuškalo has `/seller-profile` and `/seller-reviews`. Gumtree has `/seller`, `/seller-listings` and `/seller-reviews`. The reason to care: classifieds markets contain a mix of private individuals and professional dealers operating as if they were private. Listing counts per seller, review history and posting cadence separate the two. For anyone doing market analysis this is essential, because dealer pricing and private pricing follow different logic and mixing them produces a bimodal mess that averages into nonsense. It is also the basis of lead generation, which is a common use of both platforms. ## Geography Njuškalo has `/geocode` and `/reverse-geocode`. Gumtree has `/locations-autocomplete`, `/locations-nearest` for reverse geocoding a coordinate, and `/countries`. Both let you go from a coordinate to a location the platform recognises, which is what map-based search products need. Resolve to platform location IDs rather than matching place names. ## The two markets **Croatia (Njuškalo)** is the dominant marketplace in a small country, which makes it unusually complete. When one platform holds most of a national market, its listings approximate the market rather than sampling it. Cars and real estate are the deepest categories. Croatian property has a strong coastal and tourism dimension, so seasonality is real. `/popular-brands` is a useful shortcut into automotive analysis. **United Kingdom (Gumtree)** is a large, competitive market where Gumtree sits alongside eBay, Facebook Marketplace and category specialists. It is a sample of UK second-hand activity rather than the whole of it, and it is strongest in cars, home and garden, and general goods. `/similar-listings` supports recommendation features, and `/listing-by-url` handles the case where a user pastes a link. ## What people build **Price monitoring** for second-hand goods and vehicles, which requires separating dealer from private listings first. **Market intelligence.** Supply by category over time, cross-referenced against Gumtree's trending searches for the demand side. **Lead generation.** Sellers posting repeatedly in a category are businesses, and identifiable as such from listing counts and review history. **Aggregators and search products** that pull several sources into one interface. **Demand research.** Trending searches and category volume as a read on consumer intent, which moves faster than retail sales data. **Recommendation engines** built on similar-listing endpoints. ## Practical notes Normalise before you compare. Free-text titles need cleaning, and category attributes are more reliable than anything parsed out of a description. Check for a count endpoint before assuming your extraction is complete. If there is one, use it. Listings are removed as well as added. If you only ever add, your dataset will drift toward a market that no longer exists. Track disappearance as its own event, since it is a weak signal that something sold. Prices are asking prices, and on classifieds the negotiation gap is wider than in retail. ## Related APIs For another multi-vertical classifieds source with registered transaction prices, see the [Yad2 Israel API](/library/yad2-api). For UK property specifically, the [Rightmove API](/library/rightmove-uk) is deeper than Gumtree's property category. Browse the full [API Library](/library). ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by Njuškalo or Gumtree. All data is collected from publicly available sources. --- # 28Hse API: Hong Kong listings, estates and transactions Hong Kong property data is estate-centric, not address-centric. How the 28Hse API models that, and how to use estate yields and transaction records together. - Page: https://happyendpoint.com/blog/28hse-api-hong-kong-property-data - Published: 2026-08-26 - Tags: 28hse, hong-kong, real-estate, property-data, transactions Hong Kong property data does not look like property data anywhere else, and if you model it like a Western market you will get it wrong. The unit of analysis is not the address. It is the **estate**: a named residential development, often several towers and thousands of flats, where units are close to fungible. Buyers do not shop for "a two-bedroom in Kowloon". They shop for a specific estate, then a tower, then a floor, then a unit. Price per saleable square foot within one estate is remarkably tight, and comparisons across estates only make sense with the estate as the key. The [28Hse API](/library/28hse-api) is built around that model. This post covers how the pieces fit together. ## Listings, estates, and new developments Three search endpoints, and the distinction between them is the whole point. **`/property-search`** is unit-level: individual flats for sale or rent, filterable by district, estate, price, floor area and property type. This is what you show in a search interface. **`/estate-search`** is the layer above, and it is the one most people miss. It returns estates with price statistics, transaction volume and rental yield. When an investor compares two buildings rather than two flats, this is the endpoint that answers the question. It is also far more stable than unit-level data, since individual listings churn constantly while estate-level statistics move slowly and meaningfully. **`/new-property-search`** covers first-hand and pre-sale developments. In Hong Kong the primary market runs on a different logic from resale, with developer incentives, staged price lists and mortgage arrangements that do not appear in secondary listings. Keep it separate in your analysis. ## Asking prices versus transacted prices `/transactions` returns recent registered sale and lease records, optionally scoped to a single estate. This is the endpoint that makes the rest useful. Listings tell you what sellers want. Transactions tell you what buyers paid. In a market that moves as fast as Hong Kong's, the gap between the two is itself the signal - a widening spread between asking and transacted prices across an estate is a clearer read on direction than either series alone. Scoping transactions to one estate and comparing against that estate's current listings is the single most useful thing you can do with this API. ## The endpoints around the edges **`/location-autocomplete`** is the front door. Estate and district names in Hong Kong appear in English, Traditional Chinese, and several romanisations, sometimes within the same dataset. Resolve names to IDs here rather than trying to match strings yourself. Nearly every integration problem in this market traces back to name matching. **`/property-filters`** returns valid property type, sort and price-range values for a search, so you are not guessing at enum values. **`/school-net-search`** returns schools by school net, district, type and gender or religion. School nets are a genuine driver of Hong Kong residential pricing, in a way that is more explicit and more geographically rigid than catchment areas elsewhere. Estates in a desirable net carry a measurable premium. If you are modelling price, this is a real feature, not a nice-to-have. **`/mortgage-plans`** returns current bank mortgage offers with rate, cash rebate and penalty period. Hong Kong mortgage products compete on cash rebates and lock-in penalties as much as headline rate, so affordability calculators built on rate alone will misprice. **`/agent-search`** returns agency companies with per-district listing counts, and **`/service-apartment-search`** covers serviced apartments and hotels with room types and price ranges - a distinct segment serving relocation and corporate housing demand. **`/news-search`** returns property market news and video articles, useful as a sentiment or event layer over the numbers. ## Fields that behave differently here **Saleable area versus gross floor area.** Hong Kong distinguishes these sharply, and the ratio between them varies by building age and design. Since 2013, residential sales material has been required to lead with saleable area. Make sure you know which one you are reading before computing price per square foot, because mixing them produces numbers that look plausible and are wrong. **Floor matters, a lot.** Within a single tower, higher floors carry a consistent premium. A price model that ignores floor will have unexplained variance that is entirely explainable. **Tower and unit letter.** Orientation and view follow from these, and both are priced. **Age.** Hong Kong housing stock is old by international standards and building age interacts with saleable-to-gross ratio, management fees, and redevelopment potential. ## What people build **Property search products** for the local market, which need estate-first navigation rather than map-first. **Investment screening.** Rank estates by rental yield from `/estate-search`, then validate against `/transactions` for actual transacted prices rather than asking prices. **Valuation models.** Estate, tower, floor, saleable area and school net together explain a large share of price variance in a way that generic property models do not capture. **Agency and market intelligence.** Per-district listing counts by agency, tracked over time. **Relocation tools.** School nets, serviced apartments and district data combine well for corporate relocation products. ## Related APIs For other Asian property markets, see the [SUUMO Japan Real Estate API](/library/suumo-api), which has its own market-specific structure built around railway stations and commute time, or the [99.co Singapore API](/library/99co-api) covering condos, HDB flats and landed homes. Browse the [Real Estate Data hub](/real-estate-data) for the full list. ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by 28Hse. All data is collected from publicly available sources. --- # Turkey real estate data: Hepsiemlak vs Emlakjet Two Turkish property portals, two different APIs. What Hepsiemlak and Emlakjet each cover, where they overlap, and which one fits your use case. - Page: https://happyendpoint.com/blog/hepsiemlak-emlakjet-turkey-property-data - Published: 2026-08-23 - Tags: hepsiemlak, emlakjet, turkey, real-estate, property-data Turkey has two major property portals worth pulling data from, and they are not interchangeable. Hepsiemlak is the cleaner listings-and-pricing source. Emlakjet carries the analytical extras: price history, demographics, and new-construction projects. If you are covering the Turkish market, the useful question is which one answers your question, or whether you need both. ## Why Turkish property data is its own problem Three things make Turkey different from most European markets. **Inflation.** Turkish property prices have moved at rates that make nominal time series hard to read. A 40% year-on-year rise in asking price is not necessarily a real gain. Any trend analysis needs deflating or converting, and any cached price is stale faster than you expect. **Currency.** Listings are quoted in lira, but a meaningful share of demand, particularly in Istanbul and the coastal markets, is foreign and thinks in dollars or euros. The same listing tells a different story depending on the denominator. **Administrative structure.** Turkey is organised as 81 provinces (il), subdivided into districts (ilçe), then neighbourhoods (mahalle). Both APIs expose this hierarchy, and you should use it rather than free-text location matching. Turkish place names have suffixes that change with grammatical case, so string matching fails in ways that are hard to debug. ## Hepsiemlak: listings and the price index The [Hepsiemlak Turkey API](/library/hepsiemlak-api) covers 11 endpoints and is the more focused of the two. **Search.** `/search-property` filters across the country by location, price, room count, size and type. `/search-by-url` takes a Hepsiemlak search URL and returns the same results as JSON, which is the fastest way to turn an analyst's browser query into a feed. `/search-filters` returns the valid filter values so you are not guessing. **Detail.** `/property-details` and `/property-details-by-url`, with `/similar-properties` for comparables. **Geography.** `/cities`, `/counties`, `/districts` and `/locations-autocomplete` give you the full administrative tree. Resolve to IDs here first. **`/price-index`.** The endpoint that earns its place. A market price index by area, which is exactly what the raw listings cannot give you: a normalised view of where prices sit rather than what one seller is asking. In a high-inflation market this is the difference between an analysis and a number. ## Emlakjet: depth and context The [Emlakjet Turkey API](/library/emlakjet-api) runs to 18 endpoints and covers more ground. **The same core**, with `/search-property`, `/search-by-url`, `/property-details`, `/similar-listings` and the full location tree down to `/neighborhoods`. **`/price-history`.** Price changes on a specific listing over time. Reductions are a genuine signal, both of seller motivation and of where the market is turning. Most portals do not expose this at all. **`/nearby-places`.** What surrounds a property: schools, transport, hospitals, shopping. In Istanbul in particular, metro proximity is one of the strongest price determinants there is. **`/area-demographics`.** Population and demographic characteristics by area. Rare in portal APIs and useful for anything from investment screening to retail site selection. **Agencies.** `/agents-autocomplete` and `/agency-listings` cover who holds which inventory. **New construction.** `/project-search` and `/project-details` cover development projects. This matters more in Turkey than in most markets: new-build supply is a large share of transactions, sold on staged payment plans that make it a distinct product from resale. ## Choosing | You need | Use | |---|---| | Clean listings plus a market index | Hepsiemlak | | Price change history on listings | Emlakjet | | Demographics or nearby amenities | Emlakjet | | New-construction project data | Emlakjet | | Agency and inventory intelligence | Emlakjet | | Cross-checking coverage in one city | Both | For a straightforward search product, Hepsiemlak plus `/price-index` is enough. For investment analytics, Emlakjet's history and demographics carry more of the load. Running both is a reasonable coverage strategy in Istanbul, Ankara and İzmir, where inventory overlaps only partially. ## What people build **Search portals** for domestic and foreign buyers, where the foreign segment needs currency conversion at the presentation layer, not the data layer. **Investment screening.** Combine district price levels with demographics and transport proximity to rank areas, then use price history to spot where asking prices are softening. **Market monitoring.** Sample the price index on a schedule and pair it with listing volume. In an inflationary market, volume often turns before price does. **Developer and project tracking.** New-build supply by district, with pricing and delivery timelines. **Relocation and expat tools.** Neighbourhood data with amenities and transport for people who do not know the city. ## Practical notes Store the currency and the date with every price. This sounds obvious and is the single most common mistake in Turkish market analysis. Use the administrative hierarchy as your join key rather than place names. Handle both `İ` and `I` correctly - Turkish dotted and dotless i are distinct letters, and a naive `toLowerCase()` in most languages will mangle them. Treat listings as asking prices. Registered transaction data is a separate source. ## Related APIs For the wider region, see the [Aqar Saudi Arabia API](/library/aqar-api) or the [UAE Real Estate API](/library/uae-realestate-api). The [Turkey real estate data guide](/real-estate-data/turkey) covers the market page, and the [Real Estate Data hub](/real-estate-data) lists every market we carry. ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by Hepsiemlak or Emlakjet. All data is collected from publicly available sources. --- # Yad2 API: Israel property, vehicle and marketplace data Yad2 carries Israel property, cars and second-hand goods in one API, plus government-registered sale prices. What that gives you that asking prices cannot. - Page: https://happyendpoint.com/blog/yad2-api-israel-property-vehicle-data - Published: 2026-08-20 - Tags: yad2, israel, real-estate, vehicles, classifieds Most classifieds APIs give you asking prices. The [Yad2 API](/library/yad2-api) gives you asking prices **and** what properties actually sold for, because Israel publishes registered transaction prices and Yad2 surfaces them. That single difference changes what you can build. This post covers the three verticals in the API and why the transaction endpoints matter most. ## Registered sale prices Two endpoints carry the real numbers. **`/latest-deals`** returns recent government-registered completed transactions with actual sale prices. Not estimates, not asking prices - what was recorded. **`/realestate-nearby-deals`** returns registered sale prices around a specific listing. Comparable sales for the flat you are looking at. Why this is unusual: in most markets, closed transaction prices are either unavailable, expensive, or delayed by so long they are historical curiosities. The UK has Land Registry. Israel publishes to the tax authority and Yad2 makes it queryable. Spain, Turkey, the UAE and most of Asia offer nothing equivalent at this granularity. The practical consequence is that you can measure the gap between what sellers ask and what buyers pay, per neighbourhood, over time. That spread is a better read on market direction than either series alone, and it is the basis of any honest valuation model. A model trained on asking prices learns what sellers hope for. ## Real estate The property vertical runs to eleven endpoints. `/realestate-search` covers for-sale, rental and commercial listings with filters for price, rooms, floor and size, plus the amenity flags that matter locally: balcony, elevator, parking, and **mamad** - the reinforced safe room required in Israeli construction since the early 1990s. It is a genuine price factor and a genuine filter, not a curiosity. `/realestate-map` and `/realestate-map-clusters` return listing markers and area cluster counts for map interfaces, so you can render a heat view without pulling every listing. `/realestate-details` and `/realestate-details-by-url` return full ad detail, and `/realestate-search-options` returns valid filter values. Two Yad1 endpoints, `/realestate-yad1-projects` and `/realestate-yad1-nearby`, cover new construction. `/realestate-agency-promos` surfaces promoted agency inventory around a search area. ## Vehicles Seven endpoints, and this is a fuller automotive dataset than most classifieds APIs bother with. `/vehicles-search` filters by manufacturer, model and price range. `/vehicles-details` and `/vehicles-details-by-url` return full ad detail. The catalog endpoints are what make it usable at scale. `/vehicles-catalog` returns the complete manufacturer to model to sub-model tree with the IDs search expects, and `/vehicles-models` returns model master data with price ranges. Without these you are string-matching car names across Hebrew and English transliterations, which does not work. `/vehicles-agency-ads` returns other listings from the same dealer, which separates private sellers from dealers - the distinction that matters for pricing analysis. Israel's vehicle market has unusually high taxation and an unusual import structure, so local price levels and depreciation curves do not track other markets. Model it from the data rather than assuming. ## Marketplace and geography `/marketplace-listings` and `/marketplace-details` cover second-hand goods. Location data is structured across Yad2's 8 regions with `/regions`, `/cities`, `/neighborhoods` and `/locations-autocomplete`. Resolve names to IDs here - Israeli place names appear in Hebrew, English and multiple transliterations, and matching them yourself will not end well. `/categories` returns the full category tree across all verticals. ## What people build **Valuation models.** Registered transaction prices plus listing attributes is the right training set. `/realestate-nearby-deals` gives you comparables per property. **Investment analysis.** Compare asking to transacted by neighbourhood, and track the spread. Widening usually leads price moves. **Search portals** for the Israeli market, with map-based navigation from the cluster endpoints. **Automotive intelligence.** Dealer versus private pricing, model-level depreciation, inventory turnover. **Proptech and CRM enrichment.** Attach live market context and recent comparable sales to an address you already hold. ## Practical notes Hebrew is right-to-left and the API returns Hebrew text. Make sure your storage, indexing and display all handle it, and test with real data rather than Latin placeholders. Registered deals lag. Registration follows completion, which follows agreement. Expect a delay between market movement and its appearance in the transaction feed, and do not read the lag as a signal. Room counts in Israel are typically quoted including the living room and often as halves, so a "3 rooms" listing is not three bedrooms. Do not map it onto a bedroom field without converting. ## Related APIs For other multi-vertical classifieds, see the [Njuškalo Croatia API](/library/njuskalo-api) or the [Gumtree UK API](/library/gumtree-api). For dedicated property markets, browse the [Real Estate Data hub](/real-estate-data). ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by Yad2. All data is collected from publicly available sources. --- # Use any data API as an MCP server in Claude or Cursor Every Happy Endpoint API works as an MCP server through RapidAPI, with no hosting and no wrapper code. The config, what each API exposes, and what it costs. - Page: https://happyendpoint.com/blog/data-apis-as-mcp-servers - Published: 2026-08-18 - Tags: mcp, model-context-protocol, engineering, data-api, claude, agents If you are building with an AI agent and you need real data in it, the usual path is: pick an API, write a tool wrapper, describe the parameters, handle auth, keep the schema in sync. That is a day of work per API and it never stays done. For any API listed on RapidAPI, including all 27 of ours, you can skip it. RapidAPI runs an MCP gateway, and pointing it at an API turns every endpoint into an MCP tool automatically. ## What MCP is, briefly The Model Context Protocol is an open standard for connecting AI applications to external systems. An MCP server exposes **tools** the model can call, each with a name, a description and a typed parameter schema. The client handles the calling; the model just decides when a tool is useful. The point is that it is a standard. Write nothing client-specific and the same server works in Claude Desktop, Claude Code, Cursor and anything else that speaks MCP. ## The configuration One entry per API. Replace the host with whichever API you want and the key with your RapidAPI key: ```json { "mcpServers": { "happy-endpoint-bayut": { "command": "npx", "args": [ "mcp-remote", "https://mcp.rapidapi.com", "--header", "x-api-host: uae-real-estate3.p.rapidapi.com", "--header", "x-api-key: " ] } } } ``` That is the whole integration. No server to host, no wrapper to maintain, no schema to keep in sync. The `x-api-host` value is the RapidAPI host for that listing. Every one is published in our [API catalog](/api-catalog.json) and in the table at [/mcp.md](/mcp.md). ## What you actually get Each endpoint becomes one tool, with its parameters described in the tool schema. Some of ours: | API | Tools exposed | |---|---| | [Realtor.com Data API](/library/realtor-com-api) | 38 | | [Yad2 Israel API](/library/yad2-api) | 25 | | [Aqar Saudi Arabia API](/library/aqar-api) | 23 | | [Vrbo API](/library/vrbo-api) | 22 | | [Njuškalo Croatia API](/library/njuskalo-api) | 21 | | [Emlakjet Turkey API](/library/emlakjet-api) | 19 | | [Gumtree UK API](/library/gumtree-api) | 17 | | [28Hse Hong Kong API](/library/28hse-api) | 14 | Counts are from the live gateway. They run one above the endpoint count on our API pages, because the gateway also exposes each API's `status` health check, which we do not document as a product endpoint. So the Realtor.com API arrives in your client as 38 callable tools: `properties-for-sale`, `property-valuation`, `agents-search`, `mortgage-rates`, `school-district` and the rest, each with its own parameters already described. ## A worked example With the Realtor.com API connected, you can ask a question in plain language and the model works out the calls: > Find three-bedroom homes for sale in Austin under $900k that have been listed more than 60 days, and tell me what similar homes actually sold for. The model resolves the location with `locations-autocomplete`, filters with `properties-for-sale`, then pulls comparables from `properties-sold` or `similar-homes`. You did not write any of that routing. The tool descriptions carry enough for the model to sequence it. This is where MCP earns its place over a hand-written wrapper. You are not exposing one function you thought of in advance. You are exposing the whole API surface and letting the model compose it. ## What it costs Calls through the gateway count against your RapidAPI plan exactly as direct HTTP calls do. There is no MCP surcharge and no separate billing. Two practical notes: **Listing tools is free.** The `tools/list` handshake is metadata and does not consume quota, so connecting an API and inspecting what it offers costs nothing. **Watch the quota.** Agents are enthusiastic. A model exploring a 38-tool API can burn through a free tier faster than you would by hand. Every response carries `x-ratelimit-requests-remaining`, so check it early. Most of our APIs include a free tier for exactly this kind of testing. ## The limits **Only request-time APIs.** Our [bulk datasets](/datasets) and [daily data feeds](/data-feeds) are not MCP surfaces. They are files and sheets, not endpoints, and no protocol changes that. **Read-only.** These are data APIs. Nothing here books, buys or writes. **The model still needs the domain.** A tool schema tells it what parameters exist, not that Hong Kong prices are quoted on saleable area rather than gross floor area, or that Israeli room counts include the living room. Those traps are in our per-platform guides, and they are worth reading before you trust an answer. **Auth is yours.** The key in that config is a live credential. Treat the file accordingly. ## Where to start Pick an API from the [library](/library), subscribe on RapidAPI for the key, and paste the config above with that API's host. [/mcp.md](/mcp.md) lists every host and tool count in one table, and [/api-catalog.json](/api-catalog.json) has the same thing machine-readable if you would rather have your agent discover it. If you want the catalog itself in an agent, every page on this site is available as markdown by appending `.md` to its URL, and [/llms-full.txt](/llms-full.txt) is the whole thing in one document. ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by Anthropic, Cursor, or RapidAPI. MCP is an open standard; the gateway described here is RapidAPI's, and its terms and behaviour are theirs to change. --- # No public Airbnb API: short-term rental data in 2026 Airbnb has no self-serve API and applications are closed. What vacation rental data you can still get, and how Vrbo rates and availability fill the gap. - Page: https://happyendpoint.com/blog/airbnb-api-alternative-vrbo-rental-data - Published: 2026-08-16 - Tags: airbnb, vrbo, vacation-rentals, short-term-rental, travel-data Search for "Airbnb API" and you will find a developer portal, partner documentation, and a lot of blog posts explaining how to apply. What you will not find is a way to actually get a key. Airbnb has no public API. Access is limited to approved enterprise partners, mostly vetted property management systems, and the partner programme is effectively closed to unsolicited applicants. Airbnb approaches partners directly rather than the other way round. If you are building short-term rental analytics, a travel metasearch product, or a revenue tool, you are not getting in through the front door. So the practical question is not "how do I get the Airbnb API" but "what rental data can I actually get, and is it good enough". ## What short-term rental data is used for Four jobs dominate: **Rate benchmarking.** What are comparable properties charging on these dates, in this neighbourhood, at this bedroom count. Hosts and property managers use it to price; investors use it to underwrite. **Occupancy and availability analysis.** Which nights are booked across a market, how far ahead, and how that moves through the season. Availability calendars are the raw material for every occupancy estimate. **Supply and competitor tracking.** How many listings exist in a market, who runs them, how professionalised the market is, and how that changes. **Guest sentiment.** What reviewers consistently praise or complain about, which feeds both product decisions and listing optimisation. Every one of these needs the same underlying fields: nightly rates over a date range, a day-by-day availability calendar, property attributes, and reviews. None of them strictly require Airbnb specifically. They require a representative sample of the short-term rental market. ## Why Vrbo is a reasonable proxy Vrbo is one of the largest vacation rental marketplaces in the world and is owned by Expedia Group. Its inventory skews toward whole homes, which is exactly the segment most investor and revenue analysis cares about. In many leisure and coastal markets in the US and Europe, the overlap with Airbnb's whole-home inventory is substantial, and a meaningful share of properties are listed on both. That last point matters more than it sounds. In markets with heavy cross-listing, Vrbo pricing and availability track the same underlying calendar the host is managing across channels. You are not looking at a different market; you are looking at the same properties through a different window. Where it is weaker: Vrbo has proportionally less private-room and urban-apartment inventory than Airbnb. If your product is specifically about shared rooms or dense city stays, treat Vrbo as partial coverage rather than a substitute. ## What the Vrbo API gives you The [Vrbo API](/library/vrbo-api) covers 21 endpoints. The ones that matter for analytics: **Search, four ways.** By destination region, around a coordinate, inside a rectangular map bounding box, or from a pasted Vrbo search URL. All accept check-in and check-out dates, guest and pet counts, price ranges, bedroom and bathroom minimums, property types, and amenity filters. `/locations-autocomplete` turns a place name into the region ID the search endpoints need, and `/neighborhoods` narrows to named areas within a destination. **Rates for a real stay.** `/property-prices` returns bookable rate plans and the total for specific dates, not an indicative nightly figure. This distinction is the difference between a usable benchmark and a misleading one, because short-term rental pricing depends on length of stay, day of week, season, and per-property minimum-stay rules. **A day-by-day calendar.** `/property-availability` returns availability and nightly price per date. This is the endpoint occupancy models are built on. **Cancellation terms.** `/property-cancellation-policy` returns the actual refund schedule for the dates you queried, which materially affects how comparable two listings are. **Property depth.** Full detail by ID or URL, the complete amenities list, a room-by-room breakdown of beds and bathrooms, the full photo gallery grouped by room, house rules and check-in times, and location with nearby points of interest and drive times. **Reviews and hosts.** Paginated guest reviews, plus `/property-reviews-summary`, which returns a scorecard alongside an AI digest of what guests repeatedly mention. `/property-host` returns the host profile including Premier Host status and response scores, and `/host-listings` returns their other properties in the destination, which is how you separate individual hosts from professional operators. ## A worked example: benchmarking a market Say you want median nightly rate for three-bedroom homes in a coastal market over a summer weekend. 1. `/locations-autocomplete` with the destination name to get the region ID. 2. `/search` with that region, your dates, `bedrooms=3`, paging through results. 3. `/property-prices` per property for the exact dates, which gives the real bookable total rather than a headline rate. 4. Optionally `/property-availability` across a wider window to see how much of the season is already booked. The reason step 3 exists as a separate call is the reason most rate benchmarks are wrong: the number shown in search results is not the number a guest pays. Fees, length-of-stay discounts, and minimum-stay rules move it. ## What you cannot get from any of this Be clear about the limits, because they matter for what you can honestly claim. **Bookings.** No public rental API lets you create a reservation on Airbnb or Vrbo. This is listing and pricing data, not a booking channel. **Confirmed occupancy.** An unavailable night is not necessarily a booked night. Hosts block dates for personal use, maintenance, and minimum-stay mechanics. Every occupancy figure derived from calendar scraping, including from the well-known analytics vendors, is an estimate. Say so in your product. **Host identity or contact details.** Public profile information only. **Historical rates you did not collect.** These APIs return the current state. If you want a time series, you have to sample on a schedule and store it yourself. Start collecting earlier than you think you need to. ## Where this leaves you If you need Airbnb specifically and you are a property management system, apply to the partner programme and wait. For everyone else, the realistic path to short-term rental data is portal data, and the analysis you can do with a complete Vrbo picture, real bookable rates, and full availability calendars covers most of what teams actually build. The [Vrbo API](/library/vrbo-api) is on RapidAPI with a free tier. For hotel rates, flights and car rentals alongside it, see the [Priceline Pro API](/library/priceline-pro), or browse the [Travel Data hub](/travel-data). ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by Airbnb, Vrbo, or Expedia Group. All data is collected from publicly available sources. Third-party access terms are as we understood them at the time of writing and change without notice. --- # Web scraping API vs scraper API vs data API What a web scraping API actually does, how scraper APIs differ from site-specific data APIs, what each costs in engineering time, and how to pick between them. - Page: https://happyendpoint.com/blog/scraper-api-vs-site-specific-data-api - Published: 2026-08-14 - Tags: web-scraping, scraper-api, data-api, engineering, buyers-guide If your end goal is data, a web scraping API is a means, not the destination. That distinction decides which product you should be buying, and it is the thing most comparison articles skip. This guide covers what a web scraping API does, the two very different products sold under that name, and how to choose without wasting a month finding out the hard way. ## What a web scraping API does A web scraping API is an HTTP endpoint that fetches a web page for you and hands back the content, taking on the parts of scraping that break at scale: **Proxy rotation.** Requests are routed through large pools of residential, mobile or datacentre IPs so that thousands of requests do not all originate from one address and get blocked. **Browser rendering.** Many sites build their content in JavaScript, so the raw HTML is close to empty. A scraper API can run a headless browser, wait for the page to settle, and return the rendered DOM. **Anti-bot handling.** Fingerprinting, TLS signatures, behavioural checks and CAPTCHA challenges all sit between you and the page. Handling these is a specialism, and it changes constantly. **Retries and geo-targeting.** Automatic retry on soft blocks, and the ability to request a page as it appears from a specific country, which matters enormously for pricing and availability. Sold this way: ScraperAPI, Bright Data, Zyte, ZenRows, Oxylabs. You send a URL, you get HTML. That is genuinely hard infrastructure and worth paying for. But notice what you get back. **HTML.** Not data. ## The second product also called a "scraper API" A **site-specific data API** takes structured parameters for one platform and returns parsed JSON. No HTML, no selectors, no rendering. ``` GET /search-property?location=Dubai%20Marina&purpose=for-sale&beds=2 ``` ```json { "title": "2BR in Dubai Marina", "price_aed": 1850000, "beds": 2, "area_sqft": 1240, "purpose": "for-sale", "agency": { "name": "..." }, "location": { "lat": 25.077, "lng": 55.139 } } ``` `price_aed` is a number. `beds` is a number. Coordinates are parsed. Nothing in your codebase knows what the source markup looks like, so nothing in your codebase breaks when the source changes it. Both categories get called "scraper APIs" and both are legitimately that. They just stop at different points in the pipeline. ## The part that is left over If your goal is data and you buy infrastructure, the HTML arriving at your server is roughly a third of the job. What remains: **Parsing.** Someone writes and owns selectors for every field, on every page type, on every site. **Breakage.** Large sites redesign continuously, often partially and often per-region. Parsers rarely fail loudly. They silently return null for `price` on a subset of pages, and you find out from a customer. **Normalisation.** Prices arrive as `"AED 1,850,000"`, `"1.85M"` and `"1850000"` on different page types of the same site. Areas come in square feet, square metres, tsubo or ping. Dates come in four formats. All of it has to become one schema. **Pagination and result caps.** Infinite scroll, cursor tokens, and search endpoints that silently truncate at 1,000 results, so "all listings in this city" needs the query space split by price band or district before it is actually complete. **Coverage verification.** Knowing you got 40,000 of the 52,000 records that exist, and why. That work never finishes. It is a permanent maintenance cost, and it lands on the engineers who are supposed to be building your product. ## The question that decides it **How many sites, and how much do you care about the fields?** **Many sites, mostly page text** - use scraping infrastructure. News monitoring across a thousand domains, broad competitive sweeps, one-off research. No vendor can pre-build parsers for a thousand sites and you would not want them to. **A few named platforms, typed fields** - use a data API. Property listings with beds, baths, price and coordinates. Product records with brand, price, rating and stock. Anything where your application logic depends on fields being correct and consistently shaped. Most teams that end up unhappy chose infrastructure for a data-API problem, got HTML back, and discovered the actual work had not started. ## What it costs Per request, scraping infrastructure looks cheaper. That comparison ignores where the money goes. A single site parser is commonly a week of engineering to build properly, plus recurring maintenance once site changes start arriving. Multiply by platforms. Then add the failure mode that matters most: silent data quality decay, where nothing errors and your numbers are simply wrong for a while before anyone notices. The equation flips fast. One site, engineers to spare, unusual field requirements - build. Several platforms and a product to ship - buy. ## Is web scraping legal? Not legal advice, but the broad shape is worth knowing. Scraping **publicly accessible** data has repeatedly been treated more favourably by courts than scraping behind authentication. The well-known US cases turned substantially on whether access was authorised at all. Publicly visible pages sit on firmer ground than anything requiring a login. The considerations that actually matter in practice: personal data brings GDPR and similar regimes into play regardless of whether the page was public; a site's terms of service may create contractual issues distinct from computer-access law; database rights exist in the EU and apply to substantial extraction; and copyright still covers creative content such as listing photographs and written descriptions. This is a real reason teams buy rather than build. A vendor already collecting the data has made those decisions. Ask any provider what they collect and how, and if the answer is vague, that is information too. ## Choosing | Situation | Use | |---|---| | Many arbitrary domains, mostly page text | Scraping infrastructure | | A few named platforms, typed fields | Site-specific data API | | Bulk historical analysis, not live queries | A [dataset](/datasets) | | A platform nobody has built for | Build it, on scraping infrastructure | | Prototyping this week | Site-specific data API | These combine. Plenty of teams run a data API for the three platforms that carry their product and general-purpose scraping for the long tail. ## Why per-platform APIs exist Because difficulty is not uniform across sites. Property portals paginate in ways that cap results, so complete coverage of a city means splitting the search space. Retail sites vary stock and price by store and region, so one request answers less than it appears to. Classifieds sites reuse one template across cars, property and furniture with entirely different attribute sets underneath. Each is a solved problem or an unsolved one, per site. That is why the unit of the product is a platform. ## Where to start Every API in the [library](/library) is a site-specific data API for one platform, on RapidAPI, with a free tier: property, retail, grocery, travel and finance. If you want to check the data shape before writing integration code, several platforms ship [free dataset samples](/free-datasets) with the same schema as the paid data. If your question is historical rather than live, [datasets](/datasets) answer it more cheaply than any number of API calls - the [datasets versus live APIs guide](/blog/datasets-vs-live-apis-which-to-choose) covers that decision. ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by any scraping infrastructure vendor named above; they are referenced as examples of a product category. Nothing here is legal advice. --- # Zillow API alternatives in 2026: MLS access and pricing Zillow retired its public API in 2021 and Bridge Interactive is MLS-members-only. What US property data you can still get self-serve, and what it costs. - Page: https://happyendpoint.com/blog/zillow-api-alternatives-realtor-com-data - Published: 2026-08-12 - Tags: zillow, realtor-com, mls, real-estate, property-data, usa If you have tried to build anything on US residential property data in the last few years, you have hit the same wall everyone else has: there is no public Zillow API. This post covers what changed, what the remaining options actually cost, and how to get for-sale, rental, sold, and valuation data without an MLS membership. ## What happened to the Zillow API Three things, in order: **2021 - the public API was retired.** The old Zillow API, including the widely used GetSearchResults and GetZestimate endpoints, was shut down to outside developers. Anything you find referencing a Zillow API key from a tutorial written before 2021 no longer applies. **2023 - ZTRAX was discontinued.** The Zillow Transaction and Assessment Database, which academics and analysts had relied on for bulk historical records, was retired. **Now - Bridge Interactive is the only official route.** Zillow's remaining data programme runs through Bridge Interactive, and it is not aimed at developers. It requires a real estate industry affiliation, MLS membership or broker licensing, an application process measured in weeks, and pricing that typically starts around $500 per month. The practical consequence: if you are a proptech startup, an analyst, or a developer without a broker licence, the official path is closed to you. The Zestimate in particular is now surfaced only inside Zillow's own products. ## What people actually mean when they search for a "Zillow API" Almost always one of five jobs: 1. **Listing search** - homes for sale or rent in an area, with filters. 2. **Property detail** - everything known about one address. 3. **Comparable sales** - what similar homes actually sold for. 4. **A valuation** - an automated estimate of what a home is worth. 5. **Agent data** - who is selling in a market, and how active they are. Zillow is simply the most recognisable brand attached to those jobs. It is not the only source, and for four of the five it is not even the most complete one. ## The realistic options in 2026 ### Bridge Interactive (official Zillow) The only sanctioned Zillow route. Genuine MLS-grade data with genuine MLS-grade friction: licensing requirements, weeks of approval, and a floor around $500 per month. Correct choice if you are already a licensed brokerage. Not an option for most software teams. ### MLS and IDX feeds directly Going straight to the MLS gets you the underlying data Zillow itself licenses. The catch is that there are roughly 500 separate MLSs in the US, each with its own agreement, its own data dictionary, and its own approval process. RESO has standardised much of the schema, which helps, but you are still signing paperwork per market. Sensible for a regional product, painful for a national one. ### Commercial property data vendors ATTOM, CoreLogic, Estated and similar vendors sell deep public-record data: deeds, tax assessments, mortgages, ownership history. Strong for records, typically weaker on live listings, and priced for enterprise. Entry points commonly start in the hundreds per month and rise quickly with volume. ### Portal data via API Rather than fighting for MLS access, read the data from the portals that already aggregate it. This is the self-serve route: no licence, no application, no minimum contract, and you can be querying it in the time it takes to copy an API key. That is the category the [Realtor.com Data API](/library/realtor-com-api) sits in. ## What the Realtor.com Data API covers Realtor.com is the second-largest US property portal and, unlike Zillow, it is fed directly by MLS data through its operator's broker relationships. Across 37 endpoints, it maps onto all five jobs above: **Listing search.** `/properties-for-sale`, `/properties-for-rent`, and `/properties-sold` share a filter surface of roughly 97 parameters: price, beds, baths, square footage, lot size, year built, property type, HOA fees, days on market, open houses, price reductions, foreclosure status, pet policy, and more. Search geographically by radius (`/search-by-coordinates`), by a custom map polygon (`/search-by-polygon`), or by drive time from a point (`/search-by-commute`). You can also paste a Realtor.com search URL into `/search-by-url` and get the same results as JSON. **Property detail.** By property ID, by listing URL, or straight from a street address with `/property-details-by-address`, which resolves the address for you. `/property-environment` adds flood, wildfire, heat, wind, air and noise risk scores. **Comparable sales.** `/properties-sold` is the comps dataset, and `/similar-homes` returns comparables for a specific property. **Valuation.** `/property-valuation` returns the RealEstimate figure for a property across every automated valuation source it carries, with historical values and a forward forecast. This is the closest self-serve equivalent to what the Zestimate API used to provide. **Agent data.** A searchable directory with true match counts, full profiles with licence and brokerage detail, reviews and recommendations, and an agent's listings by status. Beyond the five: school and district records, current mortgage rates by ZIP, a live lender rate table, market hotness scores, neighborhood guides, geo statistics with median list, rent and sold prices, and GeoJSON boundary polygons. ## Answering the MLS question directly A common follow-up: is this MLS data? Realtor.com's listing inventory originates from MLS feeds, so for-sale and rental listings reflect what agents have published. What you do **not** get through a portal API is the private, members-only layer of an MLS: agent remarks, showing instructions, commission splits, or the ability to write back to the feed. If your product needs those, you need real MLS membership and there is no shortcut around it. For search, analytics, valuation, lead generation, and market research, the portal layer is the same data your users would see on the site, and it is available today without a licence. ## Choosing between them | You need | Route | |---|---| | Agent remarks, showing data, or write access | MLS or Bridge Interactive | | Deeds, tax assessments, ownership history | A records vendor like ATTOM or CoreLogic | | Listings, comps, valuations, agents, schools | A portal API | | One regional market, deep integration | Direct MLS or IDX feed | | National coverage, live in a day | A portal API | The honest summary: if you are licensed, use the official channels, because you can. If you are not, portal data covers most of what the old Zillow API was used for, and you can start today. ## Getting started The [Realtor.com Data API](/library/realtor-com-api) is on RapidAPI with a free tier for testing. `/locations-autocomplete` resolves a place name into the location IDs the search endpoints expect, so that is the first call to make. `/enums` returns every accepted filter value, which saves a lot of guessing against a 97-parameter search. For distressed and auction inventory, which the mainstream portals do not cover well, see the [Auction.com API](/library/auction-com-api) for foreclosure, bank-owned and auction listings with live bid status. For the wider catalog, browse the [Real Estate Data hub](/real-estate-data). ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by Zillow, Realtor.com, Move Inc., or any MLS. All data is collected from publicly available sources. Pricing and access terms for third-party services are as we understood them at the time of writing and change without notice. --- # Idealista API: property data for Spain, Italy and Portugal How to pull Idealista listings, agent data and engagement stats across three countries - the endpoints, the filters that matter, and what the data is good for. - Page: https://happyendpoint.com/blog/idealista-api-southern-europe-property-data - Published: 2026-08-10 - Tags: idealista, spain, italy, portugal, real-estate, property-data Idealista is the dominant property portal across three southern European markets at once: Spain, Italy and Portugal. That combination is unusual. Most portals are national, so covering the region normally means integrating three separate sources with three schemas. Idealista gives you one. The [Idealista API](/library/idealista-api) exposes that inventory through 14 endpoints. This post covers what is in them and what the data is actually good for. ## Finding properties: five ways in Search is where most integrations start, and there are more entry points than usual. **`/property-search`** is the standard filtered search: country, operation (sale or rent), property type, price range, size, rooms, bathrooms, condition, and the amenity flags that matter locally, such as lift, terrace, pool, garage and air conditioning. **`/smart-search`** takes natural language. You pass something like "three bedroom flat with a terrace near the beach under 400k" and it resolves the intent into a structured query. This is worth knowing about if you are building a conversational property search or an LLM agent, because it removes an entire translation layer you would otherwise write yourself. **`/property-search-by-coordinates`** searches a radius around a point, for map-driven interfaces. **`/property-search-by-zip`** searches by postal code, which is often the cleanest join key when you are enriching an existing address database. **`/property-search-by-url`** takes an Idealista search URL and returns the same results as JSON. Genuinely useful in practice: a client or analyst can build a search in the browser, send you the link, and you turn it into a feed without reverse-engineering their filters. Supporting these, `/auto-complete` resolves free text into the location IDs the search endpoints expect, `/sublocations` walks the hierarchy from region down to district, and `/reverse-geocode` turns a coordinate into an Idealista location. ## Listing detail and the endpoints people miss `/property-details` and `/property-details-by-url` return the full record: price and price history where available, surface area, floor, orientation, energy certificate rating, construction year, parking and storage, agency or private seller, photos, and geo-coordinates. Two endpoints beyond the obvious are worth calling out. **`/listing-stats`** returns engagement data for a listing - how much interest it is attracting on the portal. This is a demand signal you cannot derive from the listing itself. Two flats at the same price per square metre in the same district are not equivalent if one is generating five times the interest. For investment tools and agency dashboards, this is often the most valuable field in the response. **`/comments`** returns the listing's descriptive text and notes. Useful for keyword extraction, condition classification, and feeding text into a model that scores listings. ## Agent and agency data `/agent-details` returns an agency profile and `/agent-listings` returns its active inventory. Together they answer questions that listing data alone cannot: who is dominant in this district, how large is their book, what price bands do they operate in, and how has that changed. For lead generation and competitive analysis in Spanish and Portuguese markets, where agency structure is fragmented and local, this is usually where the commercial value sits. ## What the three markets look like **Spain** is the largest of the three by listing volume and the most liquid. Barcelona and Madrid dominate urban demand; the Balearics, Costa del Sol and Alicante carry heavy international buyer interest with different seasonality and price dynamics. Energy certificate data is well populated, which matters given EU efficiency rules tightening through the decade. **Portugal** has been reshaped by foreign demand. Lisbon and Porto have seen sustained international interest, and the Algarve behaves as a distinct holiday and second-home market rather than a residential one. Yields and price trajectories diverge sharply between them, so treat them separately in any model. **Italy** is more regionally fragmented than either. Milan and Rome behave like normal metropolitan markets. Much of the rest of the country does not, with large volumes of older housing stock, restoration properties, and enormous variation in condition at similar prices. Condition and construction-year fields do more work here than anywhere else. ## What people build with this **Cross-border property search.** The strongest use of this API specifically. One integration covering three countries lets you build a search product for buyers who are not committed to a single market, which describes most international buyers in this region. **Investment screening.** Combine price per square metre with `/listing-stats` engagement and location hierarchy to rank districts. Cross-reference against rental listings in the same area to approximate [rental yield](/dictionary/rental-yield). **Agency intelligence.** Track which agencies hold which inventory, by district and price band. **Market monitoring.** Poll saved searches on a schedule, store snapshots, and track how asking prices and inventory move. The API returns current state, so any time series is yours to build. Start collecting before you need it. **CRM and portfolio enrichment.** Use `/property-search-by-zip` or `/reverse-geocode` to attach live market context to addresses you already hold. ## Practical notes Call `/auto-complete` first and cache the location IDs. Nearly every mistake in a first integration comes from guessing at location identifiers rather than resolving them. Place names carry regional spellings, particularly in Catalonia, the Basque Country and Galicia. Do not normalise them yourself; let autocomplete do it. Treat prices as asking prices. Idealista lists what sellers want, not what buyers paid. For transacted prices you need a registry source, and in Spain that is a separate problem with its own delay. ## Related APIs For Spain specifically, the [Fotocasa API](/library/fotocasa-api) is the other major national portal and a useful cross-check on inventory and pricing. For the wider catalog see the [Real Estate Data hub](/real-estate-data), or browse the full [API Library](/library). ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by Idealista. All data is collected from publicly available sources. --- # 99.co API: Singapore property data for developers What the 99.co Singapore API covers - condos, HDB, rentals, new launches, transactions, and price trends - and how to build property apps with it. - Page: https://happyendpoint.com/blog/99co-api-singapore-property-data - Published: 2026-07-03 - Tags: 99co, singapore, real-estate, property-data, hdb Singapore is a compact but highly liquid property market, split between the public HDB segment and the private condo and landed market. Buyers and renters filter heavily by MRT access, school proximity, and new launch availability. 99.co is one of Singapore's leading property portals, and the [99.co Singapore API](/library/99co-api) gives you structured access to its listings, projects, transactions, and agent data. ## What the 99.co API covers **Property search** - filter sale and rental listings across condos, HDB flats, landed homes, and apartments. Pull full listing details by ID or directly from a 99.co listing URL, and retrieve comparable listings for "similar homes" features. **New launch and projects** - browse new launch and upcoming developments with price ranges, then get full project detail including facilities, floor plans, and active sale and rent units. New launch tracking is a core Singapore use case. **Nearby amenities** - MRT stations, schools, supermarkets, and parks for a project, with walk, drive, and taxi commute times. **Transactions and trends** - sold and rental transaction history for a project, area, or district, plus price trends and summary statistics for charts and valuation tools. **Agent directory** - search agents and pull public profiles with contact details and listing breakdowns. ## Querying the 99.co API ```js const response = await fetch( 'https://99-co-sg-api.p.rapidapi.com/search-property?' + new URLSearchParams({ listing_type: 'rent', property_type: 'condo', min_price: '3000', max_price: '6000', page: '1', }), { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': '99-co-sg-api.p.rapidapi.com', }, } ); const data = await response.json(); // listings with price, size, MRT proximity, project info, and agent details ``` Use the autocomplete endpoint first to resolve a location or project name to the IDs the search endpoints expect. ## What you can build **Property search portals** - power a Singapore-focused search UI with live listings, photos, and MRT-based filtering across both the HDB and private markets. **New launch trackers** - surface upcoming and newly launched condos with price ranges and unit availability. **Investment dashboards** - combine transaction history and price trends to estimate rental yields and flag under-priced projects, using the transaction-trends endpoint for the analytics layer. **Relocation and agent tools** - use nearby-amenity and commute data to help users compare locations, and the agent directory for lead generation. ## Coverage Nationwide Singapore coverage across the HDB towns and private residential market, including districts such as Orchard, Marina Bay, Bukit Timah, Punggol, Tampines, and Jurong. ## Evaluating before subscribing Test the 99.co Singapore API directly on RapidAPI with a free-tier subscription, and check the listing and transaction schemas against your integration before committing. View the 99.co Singapore API → · Singapore real estate data guide → --- # SUUMO API: Japan real estate and rental data What the SUUMO API covers - Japan rentals, sales, and station and commute search - and how to use it to build property search and relocation apps. - Page: https://happyendpoint.com/blog/suumo-api-japan-real-estate-data - Published: 2026-07-02 - Tags: suumo, japan, real-estate, property-data, tokyo Japan's property market does not work like Western markets. People search by railway line and station before they search by neighbourhood, commute time is often the first filter, and listings are organised around wards and prefectures rather than postcodes. SUUMO is one of Japan's largest property portals, and the [SUUMO Japan Real Estate API](/library/suumo-api) gives you structured access to its rental and sale inventory, built around those realities. ## What the SUUMO API covers **Rental and sale search** - search rentals, or buy/sell listings across used condos, houses, and land. A unified search engine lets you query across property types in one call, and count endpoints return per-ward and per-station match counts for a prefecture. **Listing details** - full detail for rentals, buy/sell listings, and new-condo projects. Each record includes layout and floor-plan information, rent or price, building details, nearest stations and walking distance, and listing media where available. **URL tools** - resolve any SUUMO URL into full structured detail, or parse it to extract the listing type and codes without fetching the record. Useful for browser extensions, lead enrichment, and internal tools where users already have a SUUMO link. **Station and commute search** - railway line and station master data by prefecture, plus a commute search that returns stations reachable within a chosen travel time and transfer count. This is the backbone of Japanese property search. **Reference and neighbourhood data** - city and ward lists, a nationwide address master, postal-code lookup, and nearby facilities returned as GeoJSON for map overlays. **Agency profiles** - real estate company and shop details by company code. ## Querying the SUUMO API ```js const response = await fetch( 'https://suumo-japan-real-estate.p.rapidapi.com/search-rentals?' + new URLSearchParams({ prefecture: 'tokyo', ward: 'shibuya', min_rent: '80000', max_rent: '150000', page: '1', }), { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'suumo-japan-real-estate.p.rapidapi.com', }, } ); const data = await response.json(); // listings with rent, layout, nearest stations, walking distance, and building details ``` Use the railway station and city endpoints first to resolve a line, station, or ward to the codes the search endpoints expect. ## What you can build **Relocation tools** - let users search homes by how far they are from a workplace station, using the commute search and station master data. This is the single most requested feature for Japan-focused housing products. **Property search apps** - power a rental or sale UI with ward and station filtering, full listing detail, and similar-listing recommendations. **Map-based discovery** - overlay listings and nearby facilities (stations, schools, shops) using the GeoJSON facility endpoint for a neighbourhood-first browsing experience. **Market analytics** - track rental and sale inventory by ward and station over time, and enrich internal databases with SUUMO listing attributes. ## Coverage Nationwide Japan coverage across prefectures, cities, and wards, including Tokyo, Osaka, Kyoto, Yokohama, Nagoya, and Fukuoka, with railway station and address-level reference data. ## Evaluating before subscribing Test the SUUMO API directly on RapidAPI with a free-tier subscription. Check the response schema for rentals and sales against your integration before committing. View the SUUMO Japan API → · Japan real estate data guide → --- # Grocery store API guide: product, price and nutrition data Which grocery APIs actually exist, what a supermarket API returns, why grocery delivery APIs are closed to developers, and how to get UK grocery data today. - Page: https://happyendpoint.com/blog/api-for-grocery-stores - Published: 2026-04-29 - Tags: grocery, supermarket, tesco, retail, price-comparison Grocery is the hardest retail category to get data out of, and the reason is structural: supermarkets treat price, promotion and availability as competitive weapons, so almost none of them publish an API. This guide covers what a grocery API returns, which routes actually exist, why the grocery delivery APIs everyone searches for are closed, and what you can integrate today. ## What a supermarket API returns Grocery data has more moving parts than most retail categories: - **Product catalog** - name, brand, category, package size, images - **Pricing** - shelf price plus unit price (per 100g, per litre), which is the only way to compare across pack sizes - **Promotions** - multi-buy mechanics ("3 for £5"), member pricing such as Tesco Clubcard, and temporary reductions - **Nutrition** - energy, fat, saturates, carbohydrates, sugars, fibre, protein and salt, per 100g and per serving, plus allergens - **Availability** - in stock or out, sometimes at store level - **Category taxonomy** - department down to sub-category Nutrition and promotions are the fields thin providers skip, and they are usually the two that matter. A price without the promotion attached is not the price a shopper pays, and a grocery product without a nutrition panel is unusable for any health or diet feature. ## Why grocery delivery APIs are closed A large share of searches for a grocery API are really looking for Instacart, Shipt, or a supermarket's own delivery platform. Those are worth addressing directly, because the answer is the same across the board. **Instacart** operates a partner platform aimed at retailers and brands running commerce integrations, not a self-serve developer API. **Shipt** is similar. Supermarkets' own ordering systems are internal. None of these hand out keys to independent developers, and the reason is commercial rather than technical: basket-level data and live delivery slots are the most sensitive things a grocer holds. So if the job is "let my users order groceries", there is no public API for that. If the job is **"know what products exist, what they cost, what promotions are running and what is in them"**, that is answerable, and it covers the large majority of what people are actually building. ## The routes that exist **Retailer-specific data APIs.** Someone builds and maintains a parser for one chain and exposes clean JSON. Deepest fields, one retailer at a time. **Cross-retailer aggregators.** Product search spanning many merchants with price comparison and history. Broader, shallower, and typically weak on nutrition. **Bulk datasets.** A full catalog snapshot as a file. Right answer for analysis and modelling, wrong answer for a live app. **Building it yourself.** Possible, and grocery sites are among the more hostile targets: heavy bot protection, store-level price and stock variation behind a postcode selector, and taxonomies that change without warning. See the [web scraping API guide](/blog/scraper-api-vs-site-specific-data-api) for what that actually costs. ## Tesco: the deepest UK grocery coverage Tesco is the UK's largest grocer at roughly 27% market share, carrying over 300,000 SKUs across the UK and Ireland. The [Tesco Data API](/library/tesco-data) is the most complete retailer-specific grocery API available on RapidAPI. Seven endpoints: - `/product-search-by-keyword` - keyword search across the catalog with pricing and images - `/product-details` - the full record, including the nutrition panel, allergens, storage and preparation - `/ireland-product-details` - the same for the Irish market, which is priced and stocked separately - `/category-page` and `/ireland-category-page` - browse by category rather than search - `/get-category-id-for-uk` and `/get-category-ids-for-ireland` - resolve the taxonomy so you are not guessing at IDs Two things worth knowing before you integrate. First, resolve category IDs before you build anything against them; the taxonomy is the part that shifts. Second, UK and Ireland are genuinely separate markets with different prices, different ranges and different promotions, which is why they have separate endpoints rather than a country parameter. Clubcard offers are the field that most distinguishes this from a generic product feed. UK grocery pricing is effectively two-tier, and a price comparison that ignores member pricing is wrong for most of Tesco's basket. A [bulk Tesco dataset](/datasets/tesco-products-uk) is also available with the full catalog including pricing, nutrition and promotional data, if your question is analytical rather than live. ## Multi-retailer coverage For price comparison across chains rather than depth on one, the [Klarna Ecom API](/library/klarna-ecom) does cross-retailer product search with price history across 13 regions. It reaches grocery categories within a much wider retail scope. Weaker on nutrition, stronger on breadth and on tracking how a price has moved. The honest position on the rest of the UK market: Asda, Ocado, Sainsbury's, Morrisons and Lidl have no comparable third-party APIs at this depth. If you need genuine multi-chain UK grocery coverage with full nutrition, no off-the-shelf product delivers it today, and you should plan for a mix of sources. ## What people build **Price comparison and basket tools.** Track a shopping list across time or retailers. Unit price is the field that makes cross-pack comparison honest, and promotions are what make it correct. **Nutrition and diet apps.** Barcode or search to a full nutrition panel with allergens. This is the use case where retailer APIs beat aggregators outright, because aggregators rarely carry the panel. **Inflation and market research.** Grocery prices are a widely watched real-economy signal. Sampling a fixed basket on a schedule gives you an observed price index rather than a reported one. **Recipe and meal planning.** Map ingredients to real purchasable products with real current prices, which turns a recipe into a costed basket. **Brand and category monitoring.** Track own-label versus brand pricing, share of shelf by category, and promotional intensity over time. **Retail media and e-commerce analytics.** Category structure and product metadata for competitive analysis. ## Practical notes **Sample on a schedule.** These APIs return current state. Price history is something you build by collecting, and every grocery analysis worth doing is longitudinal. Start earlier than you think you need to. **Store the promotion, not just the price.** A `3 for £5` mechanic and a `£1.67` shelf price are not interchangeable, and reconstructing one from the other later is impossible. **Watch pack size.** Shrinkflation is real and shows up as an unchanged price with a changed size. If you are not storing package size, you will not see it. ## Sample before you commit If you want to check the data shape before writing integration code, several platforms ship [free dataset samples](/free-datasets) with the same schema as the paid version, so your parsing code works against both. The [Tesco Data API](/library/tesco-data) is on RapidAPI with a free tier. For the wider retail catalog including IKEA, H&M and Kohl's, browse the [ecommerce data hub](/ecommerce-data) or the full [API library](/library). ## Disclaimer Happy Endpoint is not affiliated with, endorsed by, or sponsored by Tesco, Instacart, Shipt, or any retailer named here. All data is collected from publicly available sources. Third-party access terms are as we understood them at the time of writing and change without notice. --- # Bayut API: Dubai real estate data for property apps What the Bayut API covers, how to query it, and what to build with UAE property data - from search UIs to investment research tools. - Page: https://happyendpoint.com/blog/bayut-api-dubai-real-estate-data - Published: 2026-04-29 - Tags: bayut, real-estate, uae, dubai, tutorial Bayut is one of the UAE's two dominant property portals, with strong coverage across all seven emirates and a deep inventory of mid-market and affordable listings alongside premium stock. If you're building a property app, an investment tool, or a market analytics product that touches the UAE, Bayut data is one of the first sources to evaluate. This post covers what the Bayut API returns, how to structure queries, and what the most common use cases look like in practice. ## What the Bayut API covers The API serves the full Bayut listing inventory with supporting data: **Property search** - filter by emirate, area, property type (apartment, villa, penthouse, townhouse, land), transaction type (sale, rent), price range, beds, baths, and furnishing status. Results include price, property type, beds, baths, area in square feet, agent details, and listing URL. **Off-plan projects** - developer-listed off-plan projects with project name, developer, location, expected completion, price range, and available units. This is a major part of the UAE market that many data sources miss. **Agent and agency directory** - agent profiles with name, agency, listed properties count, and contact details. Useful for agent-facing tools and CRM enrichment. **Location autocomplete** - resolves to building, street, community, and emirate level. Dubai's property market uses community names (Dubai Marina, JBR, Downtown, Business Bay) more than street addresses, so this endpoint is important for any UI. **Map search** - spatial queries by bounding box or radius. Returns listings within a geographic area with coordinates. **Amenities filter** - pool, gym, parking, balcony, view type, and others. These filters matter to buyers and renters in a way that varies by property type. **Market trend data** - average price per square foot by area and property type, with trend direction. Useful for market intelligence dashboards. ## A typical property search query ```js const response = await fetch( 'https://bayut14.p.rapidapi.com/properties/list?' + new URLSearchParams({ locationExternalIDs: '5002', // Dubai Marina purpose: 'for-sale', categoryExternalID: '1', // Apartments minPrice: '1000000', maxPrice: '3000000', bedrooms: '2', hitsPerPage: '25', page: '0', lang: 'en', }), { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'bayut14.p.rapidapi.com', }, } ); const data = await response.json(); // data.hits = array of listings // data.nbHits = total matching count // data.nbPages = pagination ``` Each listing in `hits` includes the full property record: ID, title, price, area, beds, baths, agent, photos, coordinates, and amenities. ## Pagination and rate limits The Bayut API paginates via `page` and `hitsPerPage`. For a full-market backfill, iterate pages until `page >= nbPages`. For a production search UI, a single page of 25 results is usually what you need. Stay within your RapidAPI plan's request limits. For bulk operations, consider the dataset approach instead. ## What to build with Bayut data **Property search and browse** - the most direct use case. The API maps cleanly onto a filter-and-results search UI. Location autocomplete handles the input; search handles the results. **Property alerts** - poll for new listings that match saved criteria. The standard pattern: keep a set of seen listing IDs in Redis, compare each poll against that set, fire notifications for new IDs. Response times are fast enough for a 5-minute poll interval. **Investment screening** - filter listings by price-per-square-foot against the market average. Bayut's trend data gives you the benchmark; the listing data gives you the candidates. Flag properties below area average as potential value. **Off-plan tracking** - monitor new project launches and available units for a developer or area. Off-plan is a significant share of Dubai's transaction volume, especially in high-demand areas. **Agent and agency dashboards** - the agent directory lets you build tools that help estate agents manage their pipeline, track competitor listings in their area, or benchmark their own performance. **Market reporting** - aggregate listing inventory by area and price band to produce market reports. Useful for consultancies, developers, and media covering the UAE property market. ## Bayut vs PropertyFinder vs the aggregator Bayut and PropertyFinder have overlapping but not identical inventories. If you need maximum coverage, the UAE Real Estate aggregator API combines both under one key. If you need portal-specific data (agent attribution, off-plan project details native to Bayut's format), the Bayut API directly is the right choice. See the UAE real estate data guide for a side-by-side comparison. ## Start with a free evaluation The UAE real estate aggregator ships with no free sample dataset (live data only), but you can test the Bayut API directly on RapidAPI's playground with a free-tier subscription. Evaluate the schema against your use case before committing to a paid plan. View the Bayut UAE Data API → · UAE real estate data guide → --- # Fotocasa API: Spain real estate data and analytics What the Fotocasa API covers - 1.5M+ Spanish listings, market analytics, and location data - and how to use it for property search and investment research. - Page: https://happyendpoint.com/blog/fotocasa-spain-real-estate-api - Published: 2026-04-29 - Tags: fotocasa, spain, real-estate, property-data, barcelona Spain's property market is one of Europe's most active, with deep domestic demand, a large expat buyer segment, and sustained international interest in coastal and island markets. Fotocasa is the dominant Spanish property portal - the Rightmove of Spain. The Fotocasa API gives you structured access to 1.5M+ live listings across the entire country. ## What the Fotocasa API covers **Property search** - filter by location, price range, property type (apartment, house, penthouse, studio, land, commercial), transaction type (sale or rent), surface area, beds, baths, condition (new, second-hand, to rebuild), and extras (parking, storage room, swimming pool). **Location autocomplete** - resolves to municipality, neighborhood, or urbanization. Handles both Spanish and Catalan place names. Covers mainland Spain, the Balearic Islands, the Canary Islands, and Andorra. **Detailed listings** - each listing record includes: price, surface area in m2, floor number, orientation, energy certificate rating, construction year (where available), parking, storage, agency or private seller, photos, and geo-coordinates. **Market analytics** - average price per square meter by municipality or neighborhood, with trend direction (rising, stable, falling). Useful for area comparison tools, investor dashboards, and editorial content. **Real-time updates** - new listings and price changes appear in the API within minutes. Spain's market moves fast, particularly in Barcelona, Madrid, and the Balearic Islands. ## Key Spanish property markets covered **Barcelona** - the most liquid urban market in Spain. Strong demand for apartments in Eixample, Gràcia, and Poblenou. High investor and expat buyer activity. **Madrid** - the largest market by volume. Central districts (Salamanca, Chamberí, Retiro) command premium prices; surrounding commuter towns offer different yield profiles. **Valencia** - rapidly growing market. Lower prices than Madrid or Barcelona with strong rental demand from students and young professionals. **Costa del Sol (Malaga)** - primary international buyer destination. Marbella, Estepona, and Benalmadena have deep luxury and mid-market inventory. **Balearic Islands** - Mallorca, Ibiza, and Menorca. High-value, seasonal market. Ibiza commands some of the highest prices per square meter in Europe. **Seville, Bilbao, Zaragoza** - major regional capitals with distinct local market dynamics. ## Querying the Fotocasa API ```js const response = await fetch( 'https://fotocasa3.p.rapidapi.com/fotocasa/search?' + new URLSearchParams({ transactionType: 'sale', locationId: '724', // Barcelona propertyType: 'flat', minRooms: '2', maxPrice: '500000', page: '1', maxItems: '20', }), { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'fotocasa3.p.rapidapi.com', }, } ); const { realEstates } = await response.json(); // realEstates = array of listing objects // Each has: id, price, rooms, bathrooms, surface, address, coordinates, photos ``` Use the location autocomplete endpoint first to resolve a city or neighborhood name to its `locationId`. ## Use cases **International buyer tools** - many people searching Spanish property are not in Spain. An English-language product with Fotocasa's full listing inventory, local market context, and the ability to compare areas is a meaningful product gap. The market analytics endpoint gives you the area comparison layer. **Property portal** - use Fotocasa data as your listing source. Filter by region, price band, and property type; present results with photos, maps, and contact forms. **Price monitoring** - track asking price trends in a specific municipality over 3-6 months. Useful for estate agents active in Spanish markets and for investment advisors with Spanish clients. **Rental yield analysis** - Spain has strong long-term rental demand, particularly in university cities. Combine rental asking prices and sale prices in the same area to estimate [gross rental yield](/dictionary/rental-yield). **Investment screening** - filter properties where price-per-square-meter is below the area average returned by the analytics endpoint. Flag as potential value. Spain's fragmented market means undervalued properties exist even in high-demand areas. ## Fotocasa vs Spanish alternatives Idealista is the other major Spanish portal. Fotocasa has broader coverage in Catalonia; Idealista has a stronger presence in some other regions. For maximum Spain market coverage, combining both sources is the thorough approach. We provide both: see the Idealista API alongside the Fotocasa API, and Idealista also covers Italy and Portugal. ## Evaluating before subscribing Test the Fotocasa API directly on RapidAPI with a free-tier subscription. Evaluate the response schema against your integration requirements before committing. View the Fotocasa API → · Spain real estate data guide → --- # H&M fashion data API: catalog, pricing and stores What the H&M API returns - product search, pricing across 70+ markets, supplier data, and store locations - and how to use it for retail intelligence products. - Page: https://happyendpoint.com/blog/hm-fashion-data-api - Published: 2026-04-29 - Tags: hm, fashion, retail, price-monitoring, catalog H&M is one of the world's largest fashion retailers, operating in more than 70 markets with a catalog spanning clothing, accessories, beauty, and home. The H&M API gives you structured access to that catalog: product search, live pricing across markets, store locations, category browsing, and supplier information. ## What the H&M API covers **Product search** - keyword search across H&M's global catalog. Filter by category, gender (women, men, kids), age group, and market. Returns product name, price, currency, sale indicator, and product URL. **Category browsing** - H&M's category hierarchy from top-level departments (women, men, kids, home) down to sub-categories (jackets, dresses, accessories). Useful for systematic catalog ingestion and for building browse-style UIs. **Product details** - the full product record per SKU: - Name and description - Brand (H&M, H&M Home, COS, Arket, and others within the group) - Category path - Current price and sale price (where applicable) - Available colors with color names and image URLs - Available sizes and size guide - Materials composition (e.g. "100% cotton", "80% polyester, 20% elastane") - Care instructions - Product images per color **Store locator** - H&M store locations by country and city. Returns store name, address, coordinates, opening hours, and available services (click and collect, alterations). **Supplier details** - H&M's published supply chain data linked to product categories. Includes supplier facility name, country of manufacture, and compliance status. Useful for supply chain transparency products and ESG analysis. **Search autocomplete** - term suggestions for search-as-you-type functionality. ## Multi-market pricing H&M prices the same product differently across markets. Querying the API with a specific market code returns prices in local currency for that market. This makes cross-market price analysis straightforward - query the same product ID across different market codes and compare. ```js const markets = ['GB', 'US', 'SE', 'DE', 'FR']; const productId = '0992849001'; const prices = await Promise.all( markets.map(async (market) => { const res = await fetch( `https://h-m-hennes-mauritz1.p.rapidapi.com/products/${productId}?market=${market}`, { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'h-m-hennes-mauritz1.p.rapidapi.com', }, } ); const data = await res.json(); return { market, price: data.price, currency: data.currency }; }) ); // prices = [{ market: 'GB', price: 24.99, currency: 'GBP' }, ...] ``` For cross-border grey market analysis, this pattern is the foundation. ## Use cases **Price monitoring** - H&M runs frequent promotional events: seasonal sales, member-price weekdays, and category-specific markdowns. Monitoring a set of products for price drops is straightforward with the API and a simple polling loop. **Affiliate feed management** - affiliate product feeds need current prices and availability. Fashion feeds go stale fast as prices change and sizes sell out. The H&M API keeps your feed accurate. **Fashion catalog ingestion** - for comparison sites, style apps, or outfit recommendation tools that include H&M as a retailer source, the category browsing and product detail endpoints give you the full catalog. **Competitor price analysis** - if you are a fashion brand or retailer, tracking H&M's pricing on comparable product types helps you position your own pricing and monitor promotional intensity. **Supply chain transparency** - the supplier data is uncommon in retail APIs. For ESG reporting products, responsible sourcing tools, or supply chain intelligence platforms, H&M's published supplier information is a useful signal. **Multi-market retail intelligence** - H&M's global presence makes it useful as a benchmark for retail pricing across markets. A product that tracks H&M prices across regions can surface anomalies and cross-border arbitrage opportunities. ## Kohl's as a complement For the US market, the Kohl's Data API covers a different US retail segment - department store with strong private label and national brands. Pair H&M for global fashion with Kohl's for US department store depth. View the H&M API → · Fashion data API guide → --- # Klarna Ecom API: multi-store price comparison data How the Klarna Ecom API works - cross-retailer product search, price history charts, and deal tracking across 13 regions - and what to build with it. - Page: https://happyendpoint.com/blog/klarna-price-history-shopping-api - Published: 2026-04-29 - Tags: klarna, price-comparison, deals, retail, price-history The Klarna Ecom API is not Klarna's payment product. It is Klarna's product discovery infrastructure - a cross-retailer shopping API that returns product search results, price history, and deal data from multiple retailers simultaneously across 13 regions. If you are building a price comparison product, a deal discovery feed, or a consumer shopping tool that needs multi-retailer pricing in one API, this is the data source. ## What the Klarna Ecom API covers **Multi-store search** - search for a product and receive results from multiple retailers in the selected region in a single response. Each result includes product name, current price, retailer name, retailer logo, and product URL. This is the core value: one query, multiple retailer results. **Price history** - per-product historical price data showing how pricing has changed over time across retailers. Returned as a time series suitable for rendering price history charts. The "is this the lowest price in 90 days?" signal that drives purchase confidence. **Deals** - products currently at a significant discount relative to their recent price history. A deals feed surfaced to users in their region. **Product reviews** - review data from Klarna's integrated review network, linked to product records. **Category intelligence** - browse categories with multi-retailer product results rather than single-retailer catalogs. **Store data** - retailer metadata for covered merchants in each region. **13 regions** - coverage spans Europe and North America, with different retailer sets per region. ## A multi-store search query ```js const response = await fetch( 'https://klarna7.p.rapidapi.com/api/search?' + new URLSearchParams({ q: 'sony wh-1000xm5', countryCode: 'GB', size: '20', }), { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'klarna7.p.rapidapi.com', }, } ); const { products } = await response.json(); // products = array of results // Each has: name, currentPrice, retailer, url, reviewCount, reviewRating ``` To get price history for a specific product from the results: ```js const productId = products[0].id; const historyRes = await fetch( `https://klarna7.p.rapidapi.com/api/products/${productId}/price-history`, { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'klarna7.p.rapidapi.com', }, } ); const { history } = await historyRes.json(); // history = [{ date: '2025-01-15', price: 259, retailer: 'Amazon UK' }, ...] ``` ## What to build with Klarna data **Price comparison website** - the most direct use case. A user searches for a product; your app shows them where it is cheapest across all covered retailers in their region. The Klarna API provides this in one response. **Price drop alerts** - combine the price history endpoint with a target price the user sets. Poll for the product on a schedule; notify when the current price drops to or below the target. **Purchase timing advice** - show users whether now is a good time to buy. "This product is 18% below its 6-month average price" is a high-value signal. The price history data makes this a simple calculation. **Deal discovery feed** - use the deals endpoint to surface a curated feed of significant price drops across covered retailers in the user's region. Works well as a push notification, email digest, or home feed. **Affiliate comparison layer** - price comparison products that drive affiliate click-through are one of the most established e-commerce monetisation models. The Klarna API provides the comparison data; you handle the affiliate link attribution and conversion tracking. ## Region coverage The 13 supported regions span major European markets (UK, Germany, France, Sweden, Netherlands, and others) and the US. The retailer set varies by region - some are regional-only, some are pan-European or global. Check the API documentation on RapidAPI for the current region and retailer coverage list. ## Klarna as a complement to single-retailer APIs The Klarna API trades depth for breadth. It covers many retailers with standard product fields but does not return nutritional data, detailed inventory, or retailer-specific attributes that specialist APIs provide (like the Tesco API's Clubcard pricing or Kohl's review detail). For products that need single-retailer depth (a nutrition tracker needs the full Tesco nutritional panel), use the specialist API. For products that need cross-retailer comparison (a price comparison site), use Klarna. View the Klarna Ecom API → · Shopping intelligence guide → --- # Financial data API: Morningstar equities, ETFs and ESG What the Morningstar API covers - real-time quotes, financial statements, ESG risk ratings, ETF data - and how to use it in investment research and fintech products. - Page: https://happyendpoint.com/blog/morningstar-financial-data-api - Published: 2026-04-29 - Tags: morningstar, finance, investing, esg, fundamentals Morningstar is one of the most trusted names in investment research. Portfolio tools, screeners, robo-advisors, ESG reporting platforms, and financial content products all rely on the kind of institutional-quality data Morningstar provides. The Morningstar API on RapidAPI gives you that data in a developer-friendly format without negotiating a direct enterprise data contract. ## What the Morningstar API covers **Real-time quotes** - current price, volume, day range (open, high, low, close), 52-week range, and market cap for equities, ETFs, and mutual funds. Updated to reflect exchange-reported prices on the standard delay basis for each exchange. **Financial statements** - standardised income statements, balance sheets, and cash flow statements. Quarterly and annual data, typically 5+ years of history. All statements use Morningstar's standardised taxonomy, meaning the same field names apply consistently across companies and sectors. **ESG Risk Ratings** - Morningstar/Sustainalytics ESG risk scores per security and fund. Includes total ESG risk score, E/S/G component scores, controversy level, and controversy events. This is increasingly required data for institutional portfolio compliance and for any retail product with a sustainability filter. **ETF and fund data** - holdings, expense ratios, Morningstar category classification, star rating (1-5), risk-adjusted return metrics, and top-10 holdings. **Valuation metrics** - P/E ratio, price-to-book, price-to-sales, EV/EBITDA, and other standard multiples. Both trailing and forward metrics where available. **Earnings transcripts** - text of quarterly earnings call transcripts. Useful for NLP-based products that extract sentiment, guidance language, or analyst question patterns from earnings calls. **Ownership data** - institutional holder list with share counts, percentage of float held, and quarter-over-quarter change in position. **Dividend history** - dividend amounts, ex-dividend dates, and payment dates per security. Useful for income-focused screeners and dividend tracking apps. ## Building an ESG screener ```js async function screenByESG(tickers, maxRisk = 25) { const results = await Promise.all( tickers.map(async (ticker) => { const res = await fetch( `https://morningstar13.p.rapidapi.com/esg?ticker=${ticker}`, { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'morningstar13.p.rapidapi.com', }, } ); const esg = await res.json(); return { ticker, esgRisk: esg.totalEsgRiskScore, level: esg.esgRiskLevel }; }) ); return results.filter(r => r.esgRisk <= maxRisk); } // Returns only securities with ESG risk score at or below threshold // Morningstar ESG scale: <10 negligible, 10-20 low, 20-30 medium, 30-40 high, >40 severe ``` For a fund or portfolio-level ESG score, weight the individual security scores by their portfolio weight. ## Use cases **Investment screener** - filter equities or ETFs by fundamental metrics (P/E range, minimum revenue growth, debt cap), ESG score threshold, Morningstar category, and star rating. The API provides the data; your product handles the screening logic. **Portfolio analytics tool** - given a list of positions, pull quotes, sector data, and ESG scores to show portfolio composition, performance attribution, and sustainability metrics. Users increasingly expect both financial and ESG views in one product. **ESG reporting** - pull ESG risk scores for a set of holdings and produce a portfolio sustainability report. The controversy event data (from ESG response) is useful for governance-focused reporting. **Robo-advisor data layer** - fund selection rules in a robo-advisor typically depend on expense ratio, Morningstar category, star rating, and asset class. The API covers all of these. **Financial content enrichment** - enrich investment content with live data. An article about a stock that shows current price, P/E, and ESG score pulled at read time is more useful than static numbers that were accurate when the article was written. **Dividend tracking** - build an income calendar that shows upcoming ex-dividend dates and payment amounts for a user's portfolio. The dividend history endpoint provides the input data. **Earnings analysis** - combine earnings transcript text (NLP-processed for sentiment and guidance tone) with financial statement changes to build earnings-season analysis tools. ## Data freshness and coverage Real-time quotes reflect exchange-reported prices. Financial statements and ESG scores are updated when Morningstar's underlying data is refreshed - typically after earnings releases for quarterly statements and at regular intervals for ESG scores. Coverage is strongest for US-listed securities (NYSE, NASDAQ) and major international exchanges. Emerging market and small-cap coverage is thinner. View the Morningstar API → · Investment data guide → --- # Rightmove UK property data: API and dataset guide What the Rightmove UK API covers - sales, rentals, sold prices, new homes - and how to use the 5M+ transaction dataset for property analytics. - Page: https://happyendpoint.com/blog/rightmove-uk-property-data-api - Published: 2026-04-29 - Tags: rightmove, uk, real-estate, property-data, sold-prices Rightmove is the UK's largest property portal by traffic and listing volume. For any product that touches UK residential property - search, price tracking, valuation, investment research, or market analytics - Rightmove data is the primary source. There is no equivalent in terms of market penetration. The Rightmove UK API and datasets give you structured access to that inventory: live sales and rental listings, sold price history, new homes, and student accommodation. ## What the Rightmove UK API returns **Sales listings** - the full for-sale inventory with price, property type, tenure (freehold/leasehold), beds, baths, description, floor area where available, agent details, photos, and geo-coordinates. **Rental listings** - live rental inventory with asking rent per week/month, let type, deposit amount, available date, and tenant type (family, professional, student). **Sold prices** - historical transaction data accessible by property address or area. Returns sold price, date, property type, and tenure. **New homes** - properties on Rightmove's New Homes channel, listed directly by developers. Includes development name, developer, unit types, and price range. **Student housing** - purpose-built student accommodation and HMOs within range of universities. **Commercial properties** - offices, retail, industrial, and land. **Estate agent search** - find agents by location, with their listed property count. **Location autocomplete** - resolves street names, postcodes, postcode districts, and towns to Rightmove location identifiers. This is the entry point for any area-based search. All responses are structured JSON with consistent field names. The schema matches the Rightmove datasets exactly. ## Querying rental listings ```js const response = await fetch( 'https://rightmove-uk-real-estate-data.p.rapidapi.com/properties/list?' + new URLSearchParams({ locationIdentifier: 'REGION^87490', // London maxBedrooms: '2', minBedrooms: '1', propertyTypes: 'flat', maxPrice: '2500', channel: 'RENT', index: '0', sortType: '6', // most recent }), { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'rightmove-uk-real-estate-data.p.rapidapi.com', }, } ); const data = await response.json(); // data.properties = listing array // data.resultCount = total matching ``` Get the `locationIdentifier` from the autocomplete endpoint first. Rightmove uses internal region, branch, and outcode identifiers rather than standard postcodes. ## The Rightmove Sold Prices dataset The sold prices dataset is different from the API - it is a bulk file rather than a request-time lookup. - **5M+ completed transactions** - UK residential sales since records began - **Fields**: sale price, date, property type, tenure, address, and postcode - **Updates**: monthly - **Format**: JSON or CSV This is the right shape for: **Valuation model training** - the input features for an AVM are price, date, property type, floor area, and location. The sold prices dataset provides all of these at scale. Combine with the live API for current listing comparables. **Price trend analysis** - aggregate sold prices by postcode, property type, and quarter to produce indices. Useful for market reporting, investment research, and editorial content. **Area benchmarking** - given a live listing, find all comparable sold prices in the same postcode district within the last 18 months. This is the standard comparable selection methodology used by valuers. **Investment research** - calculate average hold periods, median price growth by area, and how different property types have performed over time. Free samples are available for both sales and rental listings - download them from the free samples page to evaluate the schema before committing. ## Use cases for the live API **Property search product** - the sales and rental endpoints map directly onto a standard property search UI: location input (autocomplete), filters (beds, price, type), results with photos. **Price alerts** - monitor a postcode or area for new listings below a price threshold. Poll the API on a schedule; compare new results against a seen-IDs set. **Rental yield calculator** - combine asking rent from the rental endpoint and asking price from the sales endpoint for the same area to estimate gross yield. Useful for landlord tools, buy-to-let advisors, and property investment apps. **Agent tools** - the estate agent search endpoint gives you agent metadata. Build tools that let agents track competitor listings in their patch, benchmark their stock, or monitor market time for similar properties. ## Samples before you subscribe Download the free Rightmove sales sample (5,000 London-area properties) or rental sample (3,000 properties) to evaluate the schema end-to-end. Both are at identical schema to the full paid dataset. View the Rightmove UK API → · UK property data guide → · Free samples → --- # Building a property-alerts app with the PropertyFinder API End-to-end walkthrough of a property-alerts app - poll the PropertyFinder API, deduplicate results, and notify users when new listings appear. - Page: https://happyendpoint.com/blog/building-property-alerts-app-propertyfinder-api - Published: 2026-04-28 - Tags: tutorial, propertyfinder, real-estate, alerts This post walks through a small but production-shaped app: a service that lets users subscribe to property-search criteria and notifies them when new listings match. We'll use the PropertyFinder API, but the pattern generalises. ## The shape of the problem Users save search criteria. Every few minutes, our service polls the API for each search. New listings - ones we haven't seen before - trigger notifications. Old listings (price-change updates excluded) don't. ## Architecture in one sentence A cron job per search, each poll dedupes against a seen-listings set, each new listing fires an outbox event. Keep state simple: one Redis key per search holding the set of seen listing IDs. ## Polling loop ```js async function poll(search) { const results = await fetchPropertyFinder(search.criteria); const seen = await redis.sMembers(`alerts:${search.id}:seen`); const seenSet = new Set(seen); const fresh = results.listings.filter(l => !seenSet.has(l.id)); if (fresh.length === 0) return; await redis.sAdd(`alerts:${search.id}:seen`, fresh.map(l => l.id)); await publishAlertEvents(search.userId, fresh); } ``` Three notes: - Use the listing **ID**, not a URL hash - IDs are stable. - Cap the `seen` set. Evict IDs for listings not returned in the last N polls so the set doesn't grow unbounded. - `publishAlertEvents` puts one event per new listing on your outbox. Don't send notifications synchronously from the poll loop. ## Fetching PropertyFinder Using the API from the library: ```js async function fetchPropertyFinder(criteria) { const params = new URLSearchParams({ city: criteria.city, min_price: criteria.minPrice, max_price: criteria.maxPrice, bedrooms: criteria.bedrooms, per_page: '50', }); const res = await fetch(`https://propertyfinder.p.rapidapi.com/search?${params}`, { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'propertyfinder.p.rapidapi.com', }, }); if (!res.ok) throw new Error(`PF returned ${res.status}`); return res.json(); } ``` Respect the rate limit on your plan - batch polls with a leaky bucket if you have many users. ## Cold-start: the first poll The first time a user saves a search, the poll returns dozens of listings that are "new" to us but probably not new in the world. Two options: 1. **Mark them all as seen, don't notify.** Users see alerts only for listings that appear AFTER they subscribed. Clean but a little boring for the first notification. 2. **Show them as "initial matches," notify once with a summary.** Warmer onboarding. We default to option 2 with a capped summary notification ("23 listings currently match - here are the 5 most recent"). ## Deduplication across sources (optional) If you also want to alert on Bayut, you can query Bayut in parallel. Dedupe by a canonical key (address + bedrooms + approximate area) - different platforms use different IDs, but the same listing shares canonical attributes. Or - cheaper - use the UAE aggregator which pre-dedupes across sources. ## Testing without burning rate limits Before turning on the real poll, run your whole pipeline against a free sample. The schema matches the live API, so your dedup logic, event publisher, and notification UI all work end-to-end without making a single API call. ## What not to do - Don't poll every search on a uniform 60-second schedule. Space them out (round-robin) to stay inside rate limits. - Don't notify on every field change - only "new listing appeared" and "price dropped >X%" are interesting. - Don't store full listing JSON indefinitely. IDs + timestamps + minimal metadata (price, URL) are enough. ## Next steps View the PropertyFinder API to subscribe, or read about the UAE aggregator API if you want cross-platform coverage from the start. --- # Free dataset samples: what to check in 30 minutes How to evaluate a paid dataset before you buy: schema fit, freshness, completeness, and the five quick checks that catch most quality issues. - Page: https://happyendpoint.com/blog/free-dataset-samples-evaluate-30-minutes - Published: 2026-04-26 - Tags: datasets, evaluation, free-samples, buying-guide Buying a dataset blind is the single most expensive mistake we see in the data-products space. A paid dataset that doesn't fit your use case is a sunk cost - refunds are messy, and the time you spent integrating it before realising it's wrong is gone. The fix is cheap and obvious: evaluate before you commit. Free samples exist for exactly this. This post is the evaluation playbook we recommend customers run against every paid dataset they consider - ours included. ## Why we ship samples Every dataset we sell on RapidAPI has a free, downloadable sample. Browse the full list of free samples here. Each one is structured **identically** to the paid version - same fields, same types, same edge cases. The only difference is volume: a sample is typically a few hundred to a few thousand records; the paid dataset is the full corpus. That schema parity is deliberate. It means everything you build against the sample will work against the full dataset with no code change. Your evaluation IS your integration. ## The 30-minute evaluation The framework, in five questions: ### 1. Does the schema match what I expect to query? Open the sample. Look at one record. Then look at five more. Ask: - Are the fields I need actually present? - Are types what I assumed (string vs numeric, ISO date vs unix timestamp, decimal vs string)? - Are nested objects flat enough that my downstream tools can handle them? - Are there fields you didn't expect that are valuable (or that you'll need to ignore)? This is the single highest-signal check. If the schema doesn't fit, no amount of volume will fix it. ### 2. Is the data populated, or is half of it `null`? Pick a sample of 50–100 records. Compute, per field, what fraction are non-null. The result tells you the realistic completeness you'll get at scale. A field that's 12% populated on the sample will be 12% populated in the paid dataset. If your application needs that field on every record, this is a dealbreaker - discover it now, not after purchase. ### 3. How fresh is the data? Check the timestamp on the most recent record in the sample. Compare it to today. - Same week → fresh enough for most use cases. - Last month → fine for trend analytics, marginal for current-state apps. - Older → ask the vendor about update cadence before buying. We list every dataset's update cadence on its page, but the timestamps in the sample are the truth. ### 4. Does the data look right when you eyeball it? Open 20 random records. Read them. - Does the data make sense? (No "$0" prices on premium listings, no "1970-01-01" dates, no obviously broken text encoding.) - Are there encoding issues with non-ASCII characters? - Are URLs valid and resolvable? - Are categorical fields using a consistent vocabulary, or do you see "Real Estate" / "real-estate" / "realestate" all in the same field? Five minutes of eyeballing catches data-quality issues that no amount of schema validation will surface. ### 5. Can I write my parser against the sample and have it just work? This is the integration test. Write the actual code that will consume the dataset. Run it against the sample. Verify the output is what your downstream system needs. If it works against the sample, it will work against the paid dataset - that's the whole point of schema parity. ## Red flags that should stop a purchase If any of these come up, slow down: - **Fields that should be required have inconsistent presence.** Means provenance is unreliable. - **The sample is structured differently than the paid version.** Means you can't actually validate before buying - that's a vendor process problem. - **Records reference IDs that don't resolve.** Means the dataset has dangling references to data you don't have. - **The vendor can't tell you when the next update will be cut.** Means update cadence is opportunistic, not committed. ## What we get right (and what to check for) Every Happy Endpoint dataset: - Ships a sample with **identical schema** to the paid version. - Lists **update cadence** on the dataset page. - Lists **record count** (paid version) on the dataset page. - Lists the **format** (JSONL, CSV, Parquet) so you know what your toolchain has to handle. If something in your evaluation surprises you, tell us. We'd rather flag a fit issue at the sample stage than have a customer onboard a dataset that doesn't match their use case. ## The 90-second decision If your evaluation passes all five checks: buy. If it fails one: ask the vendor. If it fails two or more: don't buy yet - either find a different source, or talk to us about a custom snapshot. A 30-minute evaluation saves you weeks of integration work against the wrong data. Browse all free samples → · Browse paid datasets → · A buyer's guide to RapidAPI data products --- # IKEA catalog data: schema, freshness and integration What's in the IKEA Pro API and catalog dataset - and the integration patterns that work for furniture retailers, comparison sites, and home-design products. - Page: https://happyendpoint.com/blog/ikea-catalog-data-furniture-retail-apps - Published: 2026-04-26 - Tags: ikea, furniture, retail, catalog, integration IKEA's catalogue is unusual in retail. The SKU set is enormous, the products themselves are durable (a BILLY bookcase from 2010 is structurally the same product today), and dimensional data - width, depth, height, weight - matters far more than for, say, fashion or grocery. If you're building a furniture comparison app, a home-design tool, an interior-style recommender, or a B2B procurement product, IKEA is one of the highest-signal sources you can ingest. This post covers what's in the IKEA Pro API and the IKEA catalog dataset, and the integration patterns that hold up at scale. ## What you actually get The IKEA data shape is broader than most retail product sources because furniture has more attributes that matter: - **Identification** - product name, IKEA article number, item type code, URL. - **Hierarchy** - series (BILLY, MALM, KALLAX), category (bookcases, beds, storage), department (living room, bedroom). - **Dimensions** - width, depth, height, weight, package count. All in real units (cm, kg). Critical for fit-checks ("does this fit in my room?"). - **Pricing** - current price by market, with currency. - **Availability** - in-stock state per market. - **Materials** - primary materials (oak, particleboard, steel) and surface treatments. - **Visuals** - gallery URLs for each product. - **Assembly** - package count and (for some products) instruction manual URLs. Every record matches the same schema across the API and dataset, so you can switch between fresh and bulk without rewriting your parser. ## Pattern 1: catalog ingestion for a comparison or design app If your app needs IKEA's full assortment available locally - searchable, filterable, joinable with other furniture sources - start with the dataset: 1. Pull the bulk catalog snapshot from the dataset. 2. Index by series and category for browse-style navigation. 3. Index by dimensions for fit-style queries ("desks under 120 cm wide"). 4. Refresh monthly. IKEA's catalogue moves slowly - daily refreshes waste API budget. 5. For the handful of products your users care about most (top sellers, watchlist items), use the live API to refresh price and stock weekly. The asymmetry - bulk for breadth, API for depth on a focused subset - is the same pattern we recommend for grocery and beauty. It costs less and feels fresher than naive uniform polling. ## Pattern 2: market expansion / multi-currency If your product runs in multiple countries, IKEA prices vary by market. The API supports per-market queries; the dataset includes a market field on each row. A few notes: - **Don't infer currency from price alone.** A `price: 49` could be EUR, GBP, USD, AED, or AED divided by 100. Always read the explicit currency field. - **Don't assume a product is sold in every market.** IKEA discontinues regionally. Check availability per market, not just globally. - **Stock state is per-market.** What's in stock in Sweden may be sold out in the UK. A pricing or comparison view that handles this correctly stands out from the dozens of half-built ones. ## Pattern 3: dimensional matching Furniture's killer feature is dimensions. Two examples worth building: - **"Will this fit?"** - user enters their room/space dimensions, your app filters the IKEA catalog to products that fit. Sort by closest fit, not just price. - **"What goes with this?"** - a user picks a sofa; your app surfaces side tables, lamps, and rugs whose dimensions are aesthetically appropriate (rough rule: side table height ≈ sofa seat height, rug width > sofa width). Both queries are trivially answered against an indexed local catalog and basically impossible from the live IKEA site without a tool layer like yours. ## Schema notes - **Article numbers are stable.** A product's `articleNumber` doesn't change across markets or over time. Use it as your primary key, not the URL. - **Series is a great join dimension.** Most users searching for "BILLY" want every BILLY variant, not just one. Index series so you can group and faceted-filter cleanly. - **Package count drives shipping cost.** A flat-pack with 4 packages is cheaper to ship than 8. If you build a delivered-cost feature, this field is essential. ## Where it fits in a broader catalog If you're building a furniture-comparison product, IKEA is one source - you'll likely want others too. The integration approach is the same: bulk dataset for breadth, live API for the subset that matters. Combine on category and dimensional attributes (the natural join keys for furniture). For the underlying decision on dataset vs API, see datasets vs live APIs: which one do you need?. For evaluation before you commit, grab the free IKEA sample - schema parity, no account required. View the IKEA Pro API → · View the IKEA catalog dataset → --- # Priceline API: hotel rates, pricing and ranking signals How to build hotel-search and travel-rate features on the Priceline API - query patterns, freshness tradeoffs, and the ranking signals that matter. - Page: https://happyendpoint.com/blog/priceline-api-travel-rate-aggregation-hotels - Published: 2026-04-26 - Tags: priceline, travel, hotels, dynamic-pricing, tutorial Travel data is harder to integrate than most retail data because almost every value is dynamic. Hotel rates change by the hour, by occupancy, by length of stay, by booking channel, and by who's asking. If you're building meta-search, a corporate-travel tool, a price-tracking product, or a travel-deals feed, you need the same query repeated against fresh data - not a static snapshot. This post covers how to use the Priceline Pro API for travel-rate aggregation, with notes on the patterns and tradeoffs that matter at scale. ## What the API gives you The Priceline Pro API surfaces what powers Priceline's own front-end: - **Hotel search** by location (city, lat/lng, point of interest), dates, occupancy, and rate filters. - **Hotel detail** - full property metadata: name, brand chain, star rating, amenities, photos, location. - **Available rates** - current rates per room type per night for a queried date range, including taxes/fees breakdowns. - **Reviews** - rating distributions and review counts per property. - **Deals** - properties currently flagged with promotional pricing. For analytical use cases (historical rate trends, seasonal pricing, market benchmarking) the Priceline hotels dataset is the right shape. The API powers live products; the dataset powers analytics. ## A typical hotel-search query ```js async function searchHotels({ city, checkIn, checkOut, adults }) { const params = new URLSearchParams({ city, checkIn, checkOut, adults: String(adults), rooms: '1', currency: 'USD', }); const res = await fetch( `https://priceline-pro.p.rapidapi.com/hotels/search?${params}`, { headers: { 'X-RapidAPI-Key': process.env.RAPIDAPI_KEY, 'X-RapidAPI-Host': 'priceline-pro.p.rapidapi.com', }, }, ); if (!res.ok) throw new Error(`Priceline returned ${res.status}`); const { properties, totalCount } = await res.json(); return properties; } ``` Three things this gets right: - **Date range, not just dates.** Hotel pricing is per-night and varies across the stay; always pass both ends. - **Currency explicit.** Don't infer from anywhere - pass it. - **Read total count.** The API paginates; if you need every match, walk pages, but most consumer-facing UIs only need the first 50–100. ## Freshness: the part everyone gets wrong The temptation is to cache aggressively. Cache too aggressively and you ship stale rates, which is the worst possible UX failure mode in travel - users see one price, click through, get a different price, lose trust. A working pattern: 1. **Cache search results for 5–15 minutes** keyed on the full query (city + dates + occupancy + filters). Same query inside the cache window returns cached. 2. **Always re-query on click-through.** If the user clicks a property, fetch fresh rates for that single property before showing the booking step. Single-property freshness is cheap; full search freshness is expensive. 3. **Surface the cache age.** "Rates from 8 minutes ago - refresh" gives users an exit and reduces complaints when prices shift. Doing the inverse (no cache, query everything live, every time) burns your rate budget for negligible UX gain. ## Ranking signals worth using The default API order is reasonable, but most products improve materially by re-ranking with a few extra signals: - **Price per night vs the market median for that city + star rating.** Surfaces real value, not just absolute cheapness. - **Review score weighted by review count.** A 4.7 with 2,000 reviews beats a 4.9 with 8 reviews almost always. - **Distance from the queried point of interest.** If the user searched "near Times Square," 500m matters more than 5km. - **Has-deal flag.** Properties currently on a promo deserve a small ranking boost (and a UI badge) - your conversion rate will thank you. Apply these as a re-ranking layer on top of what the API returns. Don't try to re-implement Priceline's full ranking; just nudge it for your audience. ## Handling availability swings Hotel availability is volatile. A property that returned rates 5 minutes ago might be sold out now. Three things to do: - **Show "X rooms left" cues only when the API surfaces them.** Don't fabricate scarcity from absence of data. - **Treat 404s on rate refresh as "no longer available," not error.** Build the UX around it: "This property just sold out - here are similar nearby options." - **Don't promise prices you can't honour.** The price you display must match the price at the booking step. If your stack can't guarantee that, surface "rates from booking partner" caveats and link directly through. ## Datasets for analytics For benchmarking, market research, or trend analysis, the Priceline hotels dataset contains historical snapshots that are impractical to reconstruct from API polling. Buy the dataset; query it with whatever you'd use for analytics (DuckDB, BigQuery, even pandas for one-off questions). For more on the choice between the two, see datasets vs live APIs. ## Try the sample first Pull a free Priceline sample before you commit. The schema matches the live API, so you can wire your full ingestion pipeline against the sample, validate it end-to-end, and only then flip the switch. View the Priceline Pro API → See also: Hotel data API guide for endpoint reference, dataset options, and more use cases. --- # Sephora product data for catalog and price monitoring Use cases for the Sephora API and US products dataset - catalog ingestion, price monitoring, and the schema patterns that fit beauty-vertical apps. - Page: https://happyendpoint.com/blog/sephora-product-data-beauty-catalog-price-monitoring - Published: 2026-04-26 - Tags: sephora, beauty, retail, price-monitoring, catalog Beauty is one of the most data-rich verticals in retail. Sephora's catalogue carries thousands of SKUs across hundreds of brands, with rich attributes - shade, finish, ingredients, claims, ratings - that drive how customers actually choose products. If your app touches beauty (search, recommendations, comparison, gifting, market research), Sephora data is one of the most useful sources you can plug in. This post covers two real-world use patterns for the Sephora API and the Sephora US products dataset: building a beauty catalogue and running a price-monitoring service. ## Use case 1: building a beauty catalogue If you're powering a search experience, a comparison site, or a "what should I buy" recommender, you need the full catalogue with rich attributes - not just price. The shape of a typical ingest: 1. **Bulk-load from the dataset.** Pull the full Sephora US products dataset. This gets you every SKU, every brand, every category, every attribute in one file. 2. **Normalise attributes per category.** Foundation has shade and finish. Fragrance has notes and concentration. Skincare has actives and skin-type tags. You'll want a per-category schema overlay so search facets are useful. 3. **Index for faceted search.** Brand, category, price band, key attributes, and ratings cover most search filters customers actually use. 4. **Refresh weekly from the dataset.** Catalogues move slowly enough that weekly is plenty. Reserve the API for the next use case. The output is a fast, faceted catalogue you control - not dependent on Sephora's site staying up or its search ranking matching your needs. ## Use case 2: price + availability monitoring For price-tracking and competitive intelligence, you want fresh data on a focused subset of SKUs. The Sephora API is the right tool here. ```js // Watch a curated set of high-priority SKUs const watched = await db.getWatchedSkus(); // your own priority list for (const sku of watched) { const fresh = await fetchSephora(`/product/${sku.id}`); if (fresh.price !== sku.lastKnownPrice) { await events.emit('priceChange', { sku: sku.id, brand: fresh.brand, from: sku.lastKnownPrice, to: fresh.price, detectedAt: new Date(), }); } if (fresh.inStock !== sku.lastKnownStockState) { await events.emit('stockChange', { sku: sku.id, state: fresh.inStock }); } } ``` What downstream services do with these events: - **Alerts** - notify users on a watchlist when a product they wanted is back in stock or has dropped in price. - **Competitive intel** - feed price changes into a dashboard your buyers/merchandisers use. - **Promo detection** - sustained price drops across a brand often indicate a promo period worth flagging. ## Catalog vs API: which one when | Need | Use | |---|---| | Full catalogue snapshot for search / recommendations | Dataset | | Fresh per-SKU price and availability | API | | Trend analytics across months of pricing | Dataset (multiple snapshots) | | Real-time alerting | API | | Bulk attribute enrichment of your existing inventory | Dataset | | One-off lookup triggered by user action | API | It's the same decision shape we cover in datasets vs live APIs - beauty-specific only because the catalogue is unusually long-lived per SKU (a foundation shade you bought 2 years ago is probably still listed today). ## Schema notes A few things specific to beauty data worth knowing: - **Shade and finish carry their own dimension.** Don't fold them into product names. They're attributes, queryable on their own. - **Ratings come with both score and count.** A 4.8 with 12 ratings means something different than a 4.8 with 12,000. Always show the count. - **Brands are a first-class attribute.** Customers search by brand far more than they realise. Index brand prominently. - **Ingredient lists are full-text.** If you're building "ingredient to avoid" filters (parabens, sulphates, fragrance), you'll want to tokenise and tag them once on ingest, not at query time. ## Compliance corner A reminder on what we cover in our compliance post: Sephora product data is publicly available - anyone can browse the site without authentication. We collect what's public and do not enrich with personal customer data. Your terms of use are with RapidAPI and us. ## Start with a sample Grab the free Sephora sample - schema matches the paid dataset and the API exactly. Half a day of evaluation will tell you whether this fits your build. View the Sephora API → · View the Sephora US products dataset → See also: Full Sephora data guide - all four datasets and the API, with use case breakdowns. --- # Tesco grocery API: product, price and stock data Using the Tesco Data API for grocery price intelligence - endpoint walkthrough, schema notes, and the patterns that hold up under real load. - Page: https://happyendpoint.com/blog/tesco-grocery-api-product-price-availability - Published: 2026-04-26 - Tags: tesco, grocery, retail, tutorial, uk-grocery UK grocery is one of the most data-heavy verticals in retail. Tesco alone publishes tens of thousands of SKUs with prices, multi-buy promotions, Clubcard offers, and stock states that all change throughout the day. If you're building price intelligence, basket optimisation, nutrition apps, or competitive monitoring, you need that data programmatically - not through screen-scraping you maintain yourself. This post walks through using the Tesco Data API on RapidAPI for production-shaped workloads. ## What the Tesco Data API gives you The endpoints cover the four data shapes most grocery products care about: - **Product search** - keyword search across the catalogue, returns IDs, names, prices, and PDP URLs. - **Categories** - the hierarchy that powers Tesco's site navigation, useful for browsing-style apps and for batch backfills. - **Nutrition** - full nutrition panel data per product. Required for any health, allergen, or diet-filter feature. - **Clubcard offers** - current promotional pricing, including multi-buy deals (the "buy 2 for £4" mechanics that drive a meaningful slice of basket value). Each response is structured JSON with stable field names. The schema matches the shape of our Tesco UK products dataset exactly - write your parser once, switch between the API and the dataset depending on whether you need fresh or bulk. ## A typical integration loop The pattern most teams converge on: ```js // 1. Pull the category tree once a week (it changes slowly) const categories = await fetchTesco('/categories'); // 2. For each category you care about, sweep products for (const cat of categories.filter(isInteresting)) { const products = await fetchTesco(`/category/${cat.id}/products`); await store.upsertMany(products); } // 3. For your high-priority SKUs (top-N by your own logic), // poll prices every few hours for (const sku of topPrioritySkus) { const fresh = await fetchTesco(`/product/${sku.id}`); if (fresh.price !== sku.lastKnownPrice) { await events.emit('priceChanged', { sku: sku.id, from: sku.lastKnownPrice, to: fresh.price }); } } ``` Three things this gets right: - **Tiered freshness.** Categories are slow-moving; product prices are fast-moving. Don't poll everything at the same cadence. - **Diff against your own state.** Don't just re-write - emit events when something actually changes, so downstream consumers (alerts, dashboards) can react. - **Top-N priority.** A grocery catalogue is long-tail. Your important SKUs are 5% of the list; spend your rate budget there. ## Schema notes that save time A few details worth knowing before your parser hits real data: - **Prices are decimals, not strings.** No locale-string parsing needed. - **Promotional pricing is a separate field.** `price` is the listed shelf price; `clubcardPrice` (when present) is the Clubcard-member price. Don't conflate them - Clubcard membership matters for analytics. - **Multi-buy deals carry their unit math.** A "2 for £4" deal returns the qualifying product, the bundle quantity, and the bundle price. You can re-derive per-unit price without parsing free text. - **Stock states are coarse.** "In stock" / "out of stock" / "low stock" - not per-store inventory counts. For store-level inventory you need a different data source. ## Rate-limit hygiene The free tier on RapidAPI is enough to validate the integration end-to-end. For production you'll likely move to a paid tier; even then, two practices keep you well-behaved: 1. **Batch your sweeps.** A category sweep at 3am UK time is cheaper and faster than 100 concurrent product calls during peak. 2. **Cache aggressively for read-heavy paths.** Most consumer apps don't need sub-minute price freshness. A 15-minute cache cuts your bill significantly. ## Where datasets fit instead If your use case is analytical - historical price trends, basket-mix research, ML training - you almost certainly want the bulk dataset, not the API. Datasets cost less per row at scale, and the schema is identical. Read more in our datasets vs APIs framework. For everything else - alerts, search, real-time dashboards, consumer-facing pricing - the API is the right shape. ## Try before you commit Download a free Tesco product sample first. The schema matches the live API, so your parser, deduper, and downstream pipeline all work end-to-end against the sample without a single API call. When you flip the switch to live, only the data source changes. View the Tesco Data API on RapidAPI → See also: UK grocery API guide for a full overview of the available endpoints and dataset options. --- # UAE real estate data: PropertyFinder vs Bayut compared Which UAE property data source fits your use case? A side-by-side look at PropertyFinder, Bayut, and the aggregator API that combines them. - Page: https://happyendpoint.com/blog/uae-real-estate-data-sources-compared - Published: 2026-04-18 - Tags: real-estate, uae, propertyfinder, bayut, comparison If you're building anything touching UAE real estate - property search, market analytics, investment research, alerting - you're picking between three practical sources: **PropertyFinder**, **Bayut**, and an **aggregator** that combines both. Happy Endpoint offers APIs and datasets for all three. Here's how to pick. ## Coverage: what each source actually has ### PropertyFinder - Deep coverage in Dubai and Abu Dhabi. - Best-in-class detail for premium listings (luxury apartments, villas). - Transaction history available in dataset form. - Source: PropertyFinder platform page ### Bayut - Strong presence across UAE emirates (not just Dubai / Abu Dhabi). - Bigger volume of mid-market and affordable listings. - Historical data available via our dataset, less deep than PropertyFinder's transactions. - Source: Bayut platform page ### UAE Real Estate aggregator - Combines PropertyFinder + Bayut + adjacent sources into a single API. - De-duplicated across platforms - the same property listed on both is returned once. - Best if you want to avoid integrating two separate APIs. - Source: UAE Real Estate platform page ## Data structure: what you get per listing Fields are similar across sources (price, bedrooms, area, agent, photos, location). Differences: - **Geocoding**: all three include lat/lng. PropertyFinder's is most precise. - **Agent metadata**: Bayut exposes agent response rate and active-listings count - useful for "trusted agent" features. - **Historical prices**: PropertyFinder dataset has multi-year price history; Bayut dataset is shorter. - **Photos**: all include galleries; Bayut returns the most per listing on average. ## When to pick which **Pick PropertyFinder** if you're: - Building a luxury / Dubai-focused product - Doing analytics on price trends (the transactions dataset is the strongest signal) - Powering a high-end search experience **Pick Bayut** if you're: - Targeting mid-market / mass affluent users - Covering emirates beyond Dubai / Abu Dhabi - Building for price-conscious segments **Pick the aggregator** if you're: - Building a meta-search (like a price-comparison site) - Running an alerting service that should fire regardless of which platform the listing appears on - Not sure and want the broadest coverage ## Pricing pattern All three APIs use RapidAPI's per-request pricing with free tiers. The aggregator is slightly more expensive per request than either PF or Bayut alone - you're paying for the dedup + merge compute. If you're serving heavy traffic and only need one source, direct is cheaper. Datasets are priced per snapshot. The PropertyFinder Transactions Dataset is typically the first dataset UAE teams buy because of its analytical depth. ## Evaluate before you commit Each platform has a free sample available. Schemas match the paid APIs exactly, so your integration code works against the sample and the live API identically. The usual evaluation flow: 1. Download the free sample for your top pick. 2. Write your parser against the sample. 3. Verify the shape is what you expected. 4. Swap the sample read for a live API call. That's a half-day evaluation for a decision that drives months of product work. ## Next step See the UAE real estate data guide, browse all real-estate sources, or tell us about your use case - we're happy to point you at the sharpest fit. --- # Datasets vs live APIs: which one do you need? Bulk snapshots and live request-time data solve different problems. A decision framework for picking the right one - or both. - Page: https://happyendpoint.com/blog/datasets-vs-live-apis-which-to-choose - Published: 2026-04-11 - Tags: datasets, apis, architecture "We need data from [platform]" is a sentence that sends you down two very different paths depending on *what you're doing with the data*. Here's a short framework for deciding. ## The core question: is the data you need a point-in-time or a stream? **Point-in-time** = a snapshot. You want every row, once. You're doing analysis, training a model, backfilling a database, or producing a report. **Stream** = live. You want fresh data on demand. You're powering a search UI, an alerting service, or a product that reflects the source platform in near-real-time. Point-in-time = dataset. Stream = API. ## When a dataset wins - **Research and analytics.** "What's the average price per square foot in Dubai Marina over the last year?" You want historical density that no API rate limit lets you pull efficiently. - **AI / ML training.** Models need volume. Datasets give you millions of rows in a single file. - **Internal dashboards.** Refresh weekly, show aggregates. You don't need per-user freshness. - **Bulk enrichment.** You have a list of 500,000 records to enrich. An API at 10 req/sec would take 14 hours; a dataset join is 30 seconds. ## When an API wins - **Customer-facing search.** Your user searched "2-bedroom Marina under 2M AED" - they expect live inventory. The listing that was available last month doesn't count. - **Alerting.** A new listing appeared in the last 15 minutes; your user needs to know. - **Price tracking.** You track current prices; historical is nice-to-have. - **On-demand lookups.** You need one record at a time, triggered by user action. ## When you need both This is common and often missed. Pattern: a dataset for the cold path (analytics, ML, bulk), an API for the hot path (live product). Example - a real-estate search product with market-trend insights: - **API**: powers the live search. PropertyFinder API returns current listings. - **Dataset**: powers the "market trends" tab. PropertyFinder Transactions Dataset has the full history. Same platform, two products, two integration patterns, one coherent customer experience. ## Cost dynamics Datasets have fixed up-front pricing - buy once, use indefinitely (within licence terms). APIs scale with usage - more users, more requests, more cost. But you're paying only for what you consume, and freshness is built in. For a dataset-heavy product (analytics, BI), datasets are almost always cheaper. For an API-heavy product (live consumer app), APIs are almost always cheaper. The hybrid approach is cheapest when you can cleanly separate cold and hot paths. ## How to decide in 90 seconds Ask: 1. Does my product break if the data is 24 hours old? → **API** 2. Will I re-query the same data repeatedly? → **Dataset** 3. Is this for analysis or training? → **Dataset** 4. Is this for a live user experience? → **API** 5. Both cold-path analytics AND hot-path UX? → **Both** ## Where to start - Browse APIs - Browse datasets - Download a free sample before committing to either Still unsure? Tell us what you're building - we'll point you at the right shape. --- # Scraping PropertyFinder data legally - and at scale What you need to know about data provenance, terms of service, and scaling web-scraped data ingestion without building your own scraper. - Page: https://happyendpoint.com/blog/scraping-propertyfinder-data-legally-at-scale - Published: 2026-04-08 - Tags: scraping, legal, compliance, propertyfinder "Can I scrape [platform] legally?" is one of the most-asked questions in the data-products space. The honest answer: it depends on your jurisdiction, your use case, and what the platform's terms say. Here's what we've learned operating at scale. ## The legal landscape, briefly In many jurisdictions, collecting **publicly available** data is generally permissible, subject to platform terms of service. Landmark cases (hiQ v. LinkedIn in the US) established that public data isn't subject to the Computer Fraud and Abuse Act, though the legal picture continues to evolve and varies significantly by country. The key concept: **publicly available** means you can view the data without logging in, without bypassing a paywall, and without circumventing technical access controls. Everything beyond that - gated content, personal data, walled-garden APIs - requires a different legal posture and usually contract negotiation with the platform. ## What this means for PropertyFinder data PropertyFinder listings are public. Anyone can visit the site without authentication, browse listings, see photos, read agent details. That's the data we serve via the PropertyFinder API and the transactions dataset. We don't scrape authenticated sections, private agent dashboards, or unposted listings. ## Scaling collection without building scrapers If you're tempted to roll your own scraping infrastructure, the operational overhead is: - **Browser automation** (Playwright, Puppeteer) to handle JavaScript-rendered pages - **Proxy rotation** to avoid IP bans - **CAPTCHA handling** when anti-bot measures trigger - **Parsing resilience** when the source HTML changes - **Rate limiting** to be polite and avoid detection - **Storage, queues, dedup** for the pipeline itself We've built all of that. That's what an API subscription gets you - someone else's headache. For an in-house team to match our collection freshness on PropertyFinder alone, you're looking at ~2 engineers full-time on pipelines that are adjacent to, not part of, your actual product. ## Compliance practices we follow - **Respect `robots.txt`** where it applies. - **Rate-limit our collection** well below the platform's apparent tolerance. - **Don't store excessive personal data.** Agent contact details on public listings are the source platform's choice to publish; we store what's there but don't enrich with external lookups. - **Allow deletion requests.** If a listing is removed from the source or an individual asks us to remove their info, we do. - **No reselling raw data as a competing product.** You can use our data internally or in products you ship; you can't rebundle it as a directly competing API. See our terms. ## What you should do If you're building on top of PropertyFinder data: 1. **Check your jurisdiction.** Data law varies significantly. Consult local counsel for high-stakes use cases. 2. **Read the PropertyFinder ToS.** If you're hitting their API or scraping their site directly, you're a party to those terms. If you're using our API, your contract is with RapidAPI and us. 3. **Design for provenance.** Keep the source and collection date with each record. Audits are easier that way. 4. **Handle deletion requests.** Build the admin flow to remove records from your system on demand, not as an afterthought. ## The easy path Skip the scraper. Subscribe on RapidAPI: - PropertyFinder API for live data - Transactions dataset for analytics Start with a free sample to evaluate the schema before subscribing. See the UAE real estate data guide for a full breakdown of what each PropertyFinder and Bayut product covers. Disclaimer: This post is general information, not legal advice. Data-scraping law is nuanced and jurisdiction-specific - always consult qualified counsel for production use cases. --- # A buyer's guide to RapidAPI data products How to evaluate paid APIs on RapidAPI without burning a week on trial subscriptions. The four questions that actually matter. - Page: https://happyendpoint.com/blog/buyers-guide-to-rapidapi-data-products - Published: 2026-04-04 - Tags: rapidapi, buying-guide, api-evaluation When you need structured data for a product you're building, RapidAPI is usually the fastest path. Thousands of APIs, unified billing, one key per service. But the signal-to-noise ratio on RapidAPI is also real - some listings are production-grade, others are hobby projects. Here's the shortlist we use when evaluating a data product before subscribing. ## 1. Is the schema stable? Look at the API's documented response. A stable schema has typed fields with consistent keys across endpoints. Red flags: fields that appear and disappear based on the request, deeply nested objects without documentation, and mixed-case keys (camelCase in one endpoint, snake_case in another). Why it matters: your parser breaks every time the shape shifts. Stable schemas mean your integration survives provider updates. ## 2. Does the free tier actually let you test? "Free tier" can mean anything from 100 requests/month (useless for real testing) to 10,000 requests/month (plenty to validate a prototype). Check: - Request count - is it enough for a realistic load test? - Endpoint coverage - does the free tier include the endpoints you actually need, or only a read-only subset? - Response size - is the payload truncated or complete? A free tier that covers your full integration for a week is worth far more than one that caps out after an hour. ## 3. What's the error contract? Make a bad request on purpose. What comes back? A production API returns structured error objects with codes, human-readable messages, and rate-limit metadata. A hobby API returns `500 Internal Server Error` with an HTML body. If the error contract isn't documented, test three failure modes yourself: - Invalid API key - Malformed parameters - Exceeded rate limit ## 4. Is the provider responsive? On RapidAPI, every listing has a Discussions tab. Skim it. Are questions from 6 months ago unanswered? That's the provider's ambient support level. Fresh, substantive answers = active maintenance. ## Happy Endpoint's posture All our APIs are listed on the library. Every listing has: - Free tier covering real-world testing volumes - Stable schema documented at docs.happyendpoint.com - Structured JSON errors with codes - Responsive maintenance - we answer Discussions questions the same week Start with the free dataset samples if you want to evaluate the data itself before committing even to a free API tier. Schema parity is guaranteed - a sample is structured identically to the full paid dataset. ## The 20-minute evaluation Before you subscribe: 1. Copy the endpoint URL. Make one request with the free tier. 2. Inspect the response. Does it look like what you'd build against? 3. Break it on purpose. How does failure surface? 4. Read the Discussions tab. Is the provider alive? Twenty minutes gets you 80% of the way to a go/no-go decision. Ready to browse? Start with the API library.