# Realtor Scraper (`crawlerbros/realtor-scraper`) Actor Scrape property listings from Realtor.com. Get prices, beds, baths, sqft, photos, agents, schools, tax history, flood/wildfire risk data, and 40+ fields per property. - **URL**: https://apify.com/crawlerbros/realtor-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Real estate, Developer tools, Other - **Stats:** 41 total users, 9 monthly users, 96.3% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 Scraper Scrape property listings from Realtor.com. Get prices, descriptions, photos, agent details, schools, tax history, flood/noise/wildfire risk data, and 40+ fields per property. Search for sale, rent, or recently sold properties. ### What is Realtor.com Property Scraper? Realtor.com Property Scraper is an Apify actor that extracts property listing data from Realtor.com. Enter a location, choose a search mode (buy, rent, or sold), and get structured data for every property — from basic listing details to comprehensive information including nearby schools, tax history, and environmental risk scores. ### Features - **Search by location** — Find properties in any US city, state, or neighborhood - **Three search modes** — For sale (BUY), for rent (RENT), or recently sold (SOLD) - **Comprehensive property data** — Price, beds, baths, sqft, lot size, year built, garage, stories - **Full descriptions** — Property marketing text and listing details - **Photo URLs** — All listing photos with direct image links - **Agent and office info** — Agent name, phone, email, and brokerage office - **Nearby schools** — School name, rating, distance, grades, and type - **Environmental risk data** — Flood factor, wildfire risk, and noise scores - **Listing history** — Price changes, sales events, and source data - **Tax history** — Assessment values, market values, and tax amounts by year - **Property features** — Cooling, heating, roofing, construction, pool, fireplace, zoning - **Direct URL support** — Paste Realtor.com property detail URLs for targeted scraping - **Automatic deduplication** — No duplicates when combining search and direct URLs ### Use Cases - **Real estate investment analysis** — Compare prices, tax history, and environmental risks - **Market research** — Track listing prices, sold prices, and days on market across neighborhoods - **Property comparison** — Side-by-side data for multiple listings in a target area - **Rental market analysis** — Compare rental prices and availability by location - **School district analysis** — Find properties near top-rated schools - **Risk assessment** — Evaluate flood, wildfire, and noise risks before buying - **Agent/broker research** — Identify active listing agents in your target market - **Data enrichment** — Augment your property database with fresh listing data ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | Search Location | String | — | City and state to search (e.g., "Houston, TX", "San Francisco, CA") | | Search Mode | Select | BUY | BUY (for sale), RENT (for rent), or SOLD (recently sold) | | Maximum Properties | Integer | 50 | Max property listings to scrape (1-500) | | Maximum Pages | Integer | 5 | Max search result pages to scrape per search (1-20) | | Scrape Full Details | Boolean | true | Fetch full detail pages for schools, history, tax, etc. Disable for faster runs. | | Start URLs | URL List | — | Direct Realtor.com property or search URLs | **Note:** At least one of **Search Location** or **Start URLs** must be provided. #### Example input — Buy properties ```json { "search": "Houston, TX", "mode": "BUY", "maxItems": 50, "scrapeDetails": true } ```` #### Example input — Rental search ```json { "search": "Miami, FL", "mode": "RENT", "maxItems": 25 } ``` #### Example input — Recently sold ```json { "search": "Denver, CO", "mode": "SOLD", "maxItems": 30 } ``` #### Example input — Direct property URLs ```json { "startUrls": [ { "url": "https://www.realtor.com/realestateandhomes-detail/123-Main-St_Houston_TX_77001_M12345-67890" } ], "scrapeDetails": true } ``` ### Output Each property produces one item in the output dataset: #### Core Property Data | Field | Type | Description | |-------|------|-------------| | url | String | Property detail URL on Realtor.com | | id | String | Realtor.com property ID | | listingId | String | MLS listing ID | | status | String | for\_sale, for\_rent, sold, pending, etc. | | listPrice | Number | Current listing price | | lastSoldPrice | Number | Last recorded sale price | | soldOn | String | Date property was last sold | | priceReduced | Number | Price reduction amount (if applicable) | | beds | Number | Number of bedrooms | | baths | String | Total bathrooms (e.g., "4.5") | | bathsFull | Number | Full bathrooms | | bathsHalf | Number | Half bathrooms | | sqft | Number | Living area in square feet | | lotSqft | Number | Lot size in square feet | | yearBuilt | Number | Year the property was constructed | | type | String | Property type (single\_family, condo, townhouse, etc.) | | subType | String | Property sub-type | | stories | Number | Number of stories | | garage | Number | Garage spaces | | name | String | Property or community name | | text | String | Full property description | | listDate | String | Date when listed | #### Location | Field | Type | Description | |-------|------|-------------| | address.street | String | Street address | | address.city | String | City | | address.state | String | State code (e.g., "TX") | | address.postalCode | String | ZIP code | | coordinates.lat | Number | Latitude | | coordinates.lng | Number | Longitude | #### Rich Data (from detail pages) | Field | Type | Description | |-------|------|-------------| | photos | Array | Photo URLs for the property | | features | Object | Property features — cooling, heating, roofing, construction, pool, fireplace, zoning | | agents | Array | Listing agents — name, phone, email, office, type | | nearbySchools | Array | Nearby schools — name, rating, distance, grades, type | | local.flood | Object | Flood factor score, severity, FEMA zone | | local.noise | Object | Noise score and categories | | local.wildfire | Object | Wildfire factor score and severity | | history | Array | Listing history — date, event, price, price per sqft | | taxHistory | Array | Tax records — year, tax amount, assessment and market values | | yearRenovated | Number | Year of last renovation | | rooms | Number | Total room count | | scrapedAt | String | ISO timestamp when data was collected | #### Sample output ```json { "url": "https://www.realtor.com/realestateandhomes-detail/46-Kingwood-Greens-Dr_Kingwood_TX_77339_M71671-24763", "id": "7167124763", "listingId": "2989700820", "status": "for_sale", "listPrice": 318000, "lastSoldPrice": null, "soldOn": "2002-01-03", "priceReduced": null, "beds": 5, "baths": "4.5", "bathsFull": null, "bathsHalf": null, "sqft": 5526, "lotSqft": 22346, "yearBuilt": 2000, "type": "single_family", "subType": "", "stories": null, "garage": 3, "name": "", "text": "Spacious 5 bedroom home in Kingwood with pool and 3-car garage...", "listDate": "2025-12-23T15:21:17.000000Z", "address": { "street": "46 Kingwood Greens Dr", "city": "Kingwood", "state": "TX", "postalCode": "77339" }, "coordinates": { "lat": 30.033194, "lng": -95.180402 }, "photos": [ "https://ap.rdcpix.com/1751b6c594d6451bf2a78323162ed623l-m1516646319s.jpg" ], "agents": [ { "name": "Lori Brown", "email": "lori.brown@rhss.com", "phone": "9792550702", "office": "REALHome Services and Solutions, Inc.", "type": "seller" } ], "features": { "cooling": "Central Air", "heating": "Central", "pool": "Yes", "roofing": "Composition" }, "nearbySchools": [ { "name": "Kingwood Park High School", "rating": 7, "distance": 1.2, "grades": ["9", "10", "11", "12"], "type": "public", "levels": ["high"], "studentCount": 2100 } ], "local": { "flood": { "floodFactorScore": 3, "severity": "Minor", "femaZone": ["X"], "insuranceRequired": "No" }, "noise": { "score": 72, "categories": ["traffic"] } }, "history": [ { "date": "2025-12-23", "event": "Listed", "price": 318000, "pricePerSqft": 58, "source": "HOTX" } ], "taxHistory": [ { "year": 2024, "tax": 8500, "assessmentTotal": 310000, "assessmentLand": 95000, "assessmentBuilding": 215000, "marketTotal": 325000, "marketLand": 100000, "marketBuilding": 225000 } ], "scrapedAt": "2026-03-25T12:00:00.000000+00:00" } ``` ### How to use #### Quick start 1. Enter a US city and state in the **Search Location** field (e.g., "Houston, TX") 2. Select a **Search Mode** — BUY, RENT, or SOLD 3. Set **Maximum Properties** to control how many listings to scrape 4. Click **Start** and wait for results #### Scrape specific properties 1. Go to [Realtor.com](https://www.realtor.com) in your browser 2. Navigate to the property listing you want 3. Copy the URL from your browser's address bar 4. Paste it into the **Start URLs** field #### Combine search and direct URLs You can provide both a location search and direct URLs. The scraper processes all sources and deduplicates results automatically. #### Faster runs without detail enrichment Set **Scrape Full Details** to `false` for a significantly faster run. You'll get core property data (price, beds, baths, sqft, address, photos, agents) from search results without visiting each property's detail page. This skips schools, tax history, listing history, risk data, and full descriptions. ### How many properties can I scrape? Realtor.com shows up to **42 properties per search page**, with a maximum of 20 pages (840 properties per search). Use the **Maximum Properties** and **Maximum Pages** inputs to control how many to scrape. ### Tips - **Start small** — Use `maxItems: 5` with `scrapeDetails: false` for your first run to verify the output format - **Disable details for speed** — Set `scrapeDetails: false` for 3-5x faster runs when you only need listing-level data - **Use specific locations** — "Houston, TX" works better than just "Houston" - **Recently sold data** — Use SOLD mode for historical price data and market analysis ### FAQ **Do I need a proxy?** The scraper automatically uses a residential proxy, which is required to access Realtor.com. This is handled internally — no configuration needed. **Why are some detail fields empty?** Detail enrichment depends on what Realtor.com provides for each listing. Not all properties have school data, tax records, or environmental risk scores. Some newer listings may not have history yet. **What's the difference between BUY, RENT, and SOLD modes?** BUY searches active for-sale listings, RENT searches rental apartments and homes, and SOLD shows recently sold properties with final sale prices. **Can I scrape a specific neighborhood or ZIP code?** Yes. Use formats like "77339" (ZIP code), "Kingwood, TX" (neighborhood + state), or a full address. **How fast is the scraper?** With details enabled: approximately 5-10 properties per minute. Without details: approximately 42 properties per page every 5-8 seconds. **Why did I get fewer properties than maxItems?** The location may have fewer listings than your limit, or the search may have reached the last page of results. # Actor input Schema ## `search` (type: `string`): City and state to search for properties (e.g., 'Houston, TX', 'San Francisco, CA', 'Miami, FL'). ## `mode` (type: `string`): Type of property search — for sale, for rent, or recently sold. ## `maxItems` (type: `integer`): Maximum number of property listings to scrape (1-500). ## `endPage` (type: `integer`): Maximum search result pages to scrape per search (1-20). Each page has up to 42 properties. ## `scrapeDetails` (type: `boolean`): Fetch each property's detail page for full description, schools, tax history, listing history, environmental risk data, and more. Disable for faster runs with only search-level data. ## `startUrls` (type: `array`): Direct Realtor.com property detail URLs or search page URLs. Paste URLs from your browser. ## Actor input object example ```json { "search": "Houston, TX", "mode": "BUY", "maxItems": 50, "endPage": 5, "scrapeDetails": true } ``` # Actor output Schema ## `properties` (type: `string`): Dataset containing scraped property listings # 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 = { "search": "Houston, TX", "maxItems": 50, "endPage": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/realtor-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 = { "search": "Houston, TX", "maxItems": 50, "endPage": 5, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/realtor-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 '{ "search": "Houston, TX", "maxItems": 50, "endPage": 5 }' | apify call crawlerbros/realtor-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/realtor-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Realtor Scraper", "description": "Scrape property listings from Realtor.com. Get prices, beds, baths, sqft, photos, agents, schools, tax history, flood/wildfire risk data, and 40+ fields per property.", "version": "1.0", "x-build-id": "JmRgvGMPl2qq1ADnB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~realtor-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-realtor-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~realtor-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-realtor-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~realtor-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-realtor-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "search": { "title": "Search Location", "type": "string", "description": "City and state to search for properties (e.g., 'Houston, TX', 'San Francisco, CA', 'Miami, FL')." }, "mode": { "title": "Search Mode", "enum": [ "BUY", "RENT", "SOLD" ], "type": "string", "description": "Type of property search — for sale, for rent, or recently sold.", "default": "BUY" }, "maxItems": { "title": "Maximum Properties", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of property listings to scrape (1-500).", "default": 50 }, "endPage": { "title": "Maximum Pages", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum search result pages to scrape per search (1-20). Each page has up to 42 properties.", "default": 5 }, "scrapeDetails": { "title": "Scrape Full Details", "type": "boolean", "description": "Fetch each property's detail page for full description, schools, tax history, listing history, environmental risk data, and more. Disable for faster runs with only search-level data.", "default": true }, "startUrls": { "title": "Start URLs", "type": "array", "description": "Direct Realtor.com property detail URLs or search page URLs. Paste URLs from your browser.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```