# Realtor.com Property Listings Scraper (`scrapeworks/realtor-property-scraper`) Actor Scrape Realtor.com listings in bulk - for-sale homes, rentals, recently sold and new construction. Get price, beds, baths, sqft, lot, year built, address, GPS, agent/brokerage, photos and status flags. Paginate deep by city, ZIP or county. No login or API key. - **URL**: https://apify.com/scrapeworks/realtor-property-scraper.md - **Developed by:** [Nicolas van Arkens](https://apify.com/scrapeworks) (community) - **Categories:** Real estate, Lead generation, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Realtor.com Property Listings Scraper Scrape real-estate listings from **Realtor.com** in bulk — **for-sale homes, rentals, recently-sold properties and new construction** — and get one clean, structured row per listing. Feed it a list of cities, ZIP codes, counties or addresses and it paginates deep automatically, returning up to ~10,000 listings per location with price, beds/baths, square footage, lot size, year built, full address, GPS coordinates, listing agent/brokerage, photos, open-house times and status flags. No login, no API key, no browser needed. This actor reads Realtor.com's own public data API, so it's fast and reliable. --- ### What you can do with it - **Real-estate lead generation** — pull every new listing in your farm area each morning (sort by *Newest*), with agent/brokerage names attached. - **Investor / iBuyer deal sourcing** — filter by price, beds and property type across dozens of ZIP codes at once; flag foreclosures, price cuts and coming-soon homes. - **Comparative market analysis (CMA) & AVM training** — pull *Recently sold* listings with sold dates to build comps and price models. - **Rental market analysis** — pull *For rent* inventory with monthly rents (and rent ranges for apartment communities) by metro. - **Market dashboards & reports** — track inventory, median price, days-on-market signals and new-construction supply across regions. --- ### Input | Field | Type | Description | |---|---|---| | `searchLocations` | array (required) | Places to scrape. Each entry is a **city + state** (`"Austin, TX"`), a **ZIP** (`"78701"`), a **county** (`"Travis County, TX"`), a neighborhood, or a street address. Add many for bulk. | | `listingType` | select | `for_sale` (default), `for_rent`, `sold` (recently sold), or `ready_to_build` (new construction). | | `sortBy` | select | `relevant` (default), `newest`, `price_low`, `price_high`, `lot_size`. | | `maxResultsPerLocation` | integer | Max listings per location (default 1000; up to ~10,000, the API's window). | | `maxResults` | integer | Optional overall cap across all locations combined. | | `priceMin` / `priceMax` | integer | Price filter (monthly rent bounds for rentals). | | `bedsMin` / `bedsMax` | integer | Bedroom filter. | | `bathsMin` | integer | Minimum bathrooms. | | `sqftMin` | integer | Minimum interior square feet. | | `propertyTypes` | array | Restrict types, e.g. `single_family`, `condo`, `townhomes`, `multi_family`, `mobile`, `land`, `farm`. | | `proxyConfiguration` | proxy | Fallback proxy (Apify Residential US by default). The actor runs direct first and only uses the proxy if a request is ever rate-limited. | #### Example input ```json { "searchLocations": ["Austin, TX", "Denver, CO", "78701"], "listingType": "for_sale", "sortBy": "newest", "maxResultsPerLocation": 1000, "priceMin": 250000, "priceMax": 750000, "propertyTypes": ["single_family", "condo"] } ```` *** ### Output One row per listing. Example (a for-sale home in Austin, TX): ```json { "propertyId": "7211899596", "listingId": "2997168140", "listingType": "for_sale", "status": "for_sale", "url": "https://www.realtor.com/realestateandhomes-detail/4719-Castleman-Dr_Austin_TX_78725_M72118-99596", "listPrice": 185000, "listPriceMin": null, "listPriceMax": null, "priceReducedAmount": null, "soldPrice": null, "soldDate": null, "beds": 3, "baths": 2, "bathsFull": 2, "bathsHalf": null, "sqft": 1405, "lotSqft": 5227, "yearBuilt": 1996, "propertyType": "single_family", "propertySubType": null, "garage": 2, "stories": 1, "streetAddress": "4719 Castleman Dr", "city": "Austin", "state": "Texas", "stateCode": "TX", "postalCode": "78725", "county": "Travis", "latitude": 30.246305, "longitude": -97.583195, "isNewListing": false, "isPriceReduced": null, "isForeclosure": null, "isNewConstruction": null, "isPending": true, "isContingent": null, "isComingSoon": null, "listDate": "2026-06-12T00:36:33.000000Z", "lastUpdateDate": "2026-06-19T19:34:09Z", "brokerName": "Keller Williams Realty", "officeName": "Keller Williams Realty", "primaryPhoto": "http://ap.rdcpix.com/7ed047f0f69ede3a6499c5571a4a6548l-m1699133238s.jpg", "photos": ["http://ap.rdcpix.com/7ed047f0f69ede3a6499c5571a4a6548l-m1699133238s.jpg"], "photoCount": 1, "virtualTourUrl": null, "streetViewUrl": "https://maps.googleapis.com/maps/api/streetview?...", "openHouseStart": null, "openHouseEnd": null, "tags": ["central_air", "central_heat", "dishwasher", "fireplace", "community_swimming_pool", "single_story", "garage_2_or_more", "new_roof"], "searchLocation": "Austin, TX", "resultPosition": 1, "scrapedAt": "2026-07-19T13:51:43Z" } ``` #### Field notes - **Price by listing type:** for **sale** and **new construction**, `listPrice` is the asking price. For **rentals**, `listPrice` is the **monthly rent**; apartment *communities* instead carry a rent **range** in `listPriceMin` / `listPriceMax` (single `listPrice` is null for those). For **recently sold**, `listPrice` is the last asking price and `soldDate` is the closing date (`soldPrice` is present when Realtor.com discloses it — it is not disclosed for every sale). - **Photos** are returned up to 25 per listing; `photoCount` is how many came back. - Status flags (`isForeclosure`, `isPriceReduced`, `isComingSoon`, …) are `true`/`false` when set and `null` when Realtor.com doesn't flag that condition — a `null` means "not flagged", not an error. *** ### How pagination & scale work Realtor.com serves 200 listings per API page and exposes up to a **~10,000-result window per search location**. The actor pages through that window automatically for every location you provide. To pull an entire large metro, split it by ZIP codes or counties and pass them all in `searchLocations` — each is scraped to its own depth, so the total is unbounded by the per-location window. ### FAQ **Do I need a Realtor.com login or API key?** No. The actor reads Realtor.com's public listing data directly. **Is scraping Realtor.com allowed?** This actor collects only publicly visible listing data. You are responsible for using the data in line with Realtor.com's terms and applicable law (e.g. don't resell MLS-restricted data or spam agents). **How fresh is the data?** It's pulled live from Realtor.com at run time, so it reflects the current listings shown on the site. **Why are some fields null?** Not every listing publishes every field (e.g. lot size, garage, sold price). A `null` means Realtor.com didn't provide that value for that listing. **How am I billed?** Pay-per-result: you're charged once for each listing returned. Blocked or empty pages are never charged. # Actor input Schema ## `searchLocations` (type: `array`): One or more places to pull listings from. Each entry can be a city + state ("Austin, TX"), a ZIP code ("78701"), a county ("Travis County, TX"), a neighborhood, or a street address. Every location is paginated DEEP automatically (200 listings per page, up to Realtor.com's ~10,000-result window per location), so a handful of metros returns tens of thousands of listings. Results are billed per listing, so more locations = more rows. ## `listingType` (type: `string`): Which listings to pull. 'For sale' = homes on the market; 'For rent' = rentals (the price field is the monthly rent); 'Recently sold' = sold homes (soldPrice/soldDate populated, listPrice is the last asking price); 'New construction' = ready-to-build / builder listings. ## `sortBy` (type: `string`): Order listings within each location. 'Most relevant' is Realtor.com's default ranking; 'Newest' returns freshly-listed homes first (great for lead-gen); 'Price low/high' and 'Largest lot' sort by those fields. ## `maxResultsPerLocation` (type: `integer`): Maximum listings to return for EACH search location. The actor paginates automatically (200 per page). Realtor.com's API exposes up to ~10,000 results per location; set high to pull a whole metro, lower it to sample. Every listing returned is billed. ## `maxResults` (type: `integer`): Optional overall cap across ALL locations combined. Leave empty for no overall cap (each location is still bounded by Max results per location). Useful to cap the total billed rows for a run. ## `priceMin` (type: `integer`): Only return listings at or above this price. For rentals this is the minimum monthly rent. Leave empty for no lower bound. ## `priceMax` (type: `integer`): Only return listings at or below this price. For rentals this is the maximum monthly rent. Leave empty for no upper bound. ## `bedsMin` (type: `integer`): Only return listings with at least this many bedrooms. Leave empty for any. ## `bedsMax` (type: `integer`): Only return listings with at most this many bedrooms. Leave empty for any. ## `bathsMin` (type: `integer`): Only return listings with at least this many bathrooms. Leave empty for any. ## `sqftMin` (type: `integer`): Only return listings with at least this interior square footage. Leave empty for any. ## `propertyTypes` (type: `array`): Restrict to specific property types. Common values: single\_family, condo, townhomes, multi\_family, mobile, land, farm, condos. Leave empty for all types. ## `proxyConfiguration` (type: `object`): Fallback proxy for reaching Realtor.com's API. The actor sends requests DIRECTLY first (the GraphQL API answers datacenter requests fine, so no proxy is needed on the happy path) and only routes through this proxy - rotating exits - if a request is ever rate-limited. The default (Apify Residential, US) is a safe fallback; leave it in place. ## Actor input object example ```json { "searchLocations": [ "Austin, TX", "Denver, CO", "78701", "Miami-Dade County, FL" ], "listingType": "for_sale", "sortBy": "relevant", "maxResultsPerLocation": 1000, "propertyTypes": [ "single_family", "condo", "townhomes" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchLocations": [ "Austin, TX" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }; // Run the Actor and wait for it to finish const run = await client.actor("scrapeworks/realtor-property-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchLocations": ["Austin, TX"], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US", }, } # Run the Actor and wait for it to finish run = client.actor("scrapeworks/realtor-property-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchLocations": [ "Austin, TX" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }' | apify call scrapeworks/realtor-property-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapeworks/realtor-property-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Realtor.com Property Listings Scraper", "description": "Scrape Realtor.com listings in bulk - for-sale homes, rentals, recently sold and new construction. Get price, beds, baths, sqft, lot, year built, address, GPS, agent/brokerage, photos and status flags. Paginate deep by city, ZIP or county. No login or API key.", "version": "0.1", "x-build-id": "iFqGVZw1CC8nhqcBh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapeworks~realtor-property-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapeworks-realtor-property-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapeworks~realtor-property-scraper/runs": { "post": { "operationId": "runs-sync-scrapeworks-realtor-property-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapeworks~realtor-property-scraper/run-sync": { "post": { "operationId": "run-sync-scrapeworks-realtor-property-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchLocations" ], "properties": { "searchLocations": { "title": "Search locations", "uniqueItems": true, "type": "array", "description": "One or more places to pull listings from. Each entry can be a city + state (\"Austin, TX\"), a ZIP code (\"78701\"), a county (\"Travis County, TX\"), a neighborhood, or a street address. Every location is paginated DEEP automatically (200 listings per page, up to Realtor.com's ~10,000-result window per location), so a handful of metros returns tens of thousands of listings. Results are billed per listing, so more locations = more rows.", "items": { "type": "string" } }, "listingType": { "title": "Listing type", "enum": [ "for_sale", "for_rent", "sold", "ready_to_build" ], "type": "string", "description": "Which listings to pull. 'For sale' = homes on the market; 'For rent' = rentals (the price field is the monthly rent); 'Recently sold' = sold homes (soldPrice/soldDate populated, listPrice is the last asking price); 'New construction' = ready-to-build / builder listings.", "default": "for_sale" }, "sortBy": { "title": "Sort by", "enum": [ "relevant", "newest", "price_low", "price_high", "lot_size" ], "type": "string", "description": "Order listings within each location. 'Most relevant' is Realtor.com's default ranking; 'Newest' returns freshly-listed homes first (great for lead-gen); 'Price low/high' and 'Largest lot' sort by those fields.", "default": "relevant" }, "maxResultsPerLocation": { "title": "Max results per location", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum listings to return for EACH search location. The actor paginates automatically (200 per page). Realtor.com's API exposes up to ~10,000 results per location; set high to pull a whole metro, lower it to sample. Every listing returned is billed.", "default": 1000 }, "maxResults": { "title": "Max results overall (optional)", "minimum": 1, "maximum": 500000, "type": "integer", "description": "Optional overall cap across ALL locations combined. Leave empty for no overall cap (each location is still bounded by Max results per location). Useful to cap the total billed rows for a run." }, "priceMin": { "title": "Min price (optional)", "minimum": 0, "type": "integer", "description": "Only return listings at or above this price. For rentals this is the minimum monthly rent. Leave empty for no lower bound." }, "priceMax": { "title": "Max price (optional)", "minimum": 0, "type": "integer", "description": "Only return listings at or below this price. For rentals this is the maximum monthly rent. Leave empty for no upper bound." }, "bedsMin": { "title": "Min bedrooms (optional)", "minimum": 0, "type": "integer", "description": "Only return listings with at least this many bedrooms. Leave empty for any." }, "bedsMax": { "title": "Max bedrooms (optional)", "minimum": 0, "type": "integer", "description": "Only return listings with at most this many bedrooms. Leave empty for any." }, "bathsMin": { "title": "Min bathrooms (optional)", "minimum": 0, "type": "integer", "description": "Only return listings with at least this many bathrooms. Leave empty for any." }, "sqftMin": { "title": "Min square feet (optional)", "minimum": 0, "type": "integer", "description": "Only return listings with at least this interior square footage. Leave empty for any." }, "propertyTypes": { "title": "Property types (optional)", "uniqueItems": true, "type": "array", "description": "Restrict to specific property types. Common values: single_family, condo, townhomes, multi_family, mobile, land, farm, condos. Leave empty for all types.", "items": { "type": "string" } }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Fallback proxy for reaching Realtor.com's API. The actor sends requests DIRECTLY first (the GraphQL API answers datacenter requests fine, so no proxy is needed on the happy path) and only routes through this proxy - rotating exits - if a request is ever rate-limited. The default (Apify Residential, US) is a safe fallback; leave it in place.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```