# Realtor.com Scraper - Properties, Prices & Agent Leads (`scrapesage/realtor-com-scraper`) Actor Scrape Realtor.com for-sale, for-rent & sold listings — prices, beds/baths, sqft, photos, MLS, geo, schools, price & tax history — plus deduped real-estate agent & office leads with email, phone & website. Keyless, no browser. Filter by location, price & type; monitor new listings & price drops. - **URL**: https://apify.com/scrapesage/realtor-com-scraper.md - **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community) - **Categories:** Real estate, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 1,000 property listings 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.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 Scraper — Properties, Prices & Agent Leads Extract **complete Realtor.com property data** — for-sale, for-rent and recently-sold listings with **real prices, beds/baths, square footage, lot size, MLS number, full address with geo, photos, schools, and complete price & tax history**. Then turn every listing agent and office into a **ready-to-contact B2B lead** with **direct email, phone, personal website and brokerage** — deduped and lead-scored. No login, no cookies, no browser — fast JSON extraction straight from Realtor.com's own property API, with 98%+ reliability. ### Why this Realtor.com scraper? Most Realtor.com scrapers either return thin card data or charge a per-run start fee. This actor pulls from Realtor.com's internal GraphQL API and ships the **richest dataset in the category — with no start fee**: | Data | Typical scrapers | This actor | |---|---|---| | List price, beds, baths, sqft, lot size | ✅ | ✅ | | For-sale **and** for-rent **and** sold (comps) | partial | ✅ all three | | MLS number, listing ID, source | ❌ | ✅ | | Full address + lat/long + county + neighborhood | partial | ✅ | | Listing **agent email + phone + website** | ❌ | ✅ | | Deduped **agent / office leads** with lead score | ❌ | ✅ | | Assigned **schools with ratings** | ❌ | ✅ opt-in | | Full **listing & price history** | ❌ | ✅ opt-in | | Multi-year **tax & assessment history** | ❌ | ✅ opt-in | | Complete feature list (interior/exterior/utilities) | ❌ | ✅ opt-in | | Only-new / price-drop **monitor mode** | ❌ | ✅ | | Per-run start fee | 💸 often | ✅ none | ### Use cases - **Real-estate agent lead generation** — every active listing carries its listing agent's **name, email, phone, website and brokerage**. Deduped and scored, that's a fresh, targeted agent database for CRMs, recruiting brokerages, title/escrow, mortgage, transaction-coordination, photography, staging and proptech vendors. - **Investor deal-flow & comps** — pull for-sale inventory and recently-sold comparables (with sold dates and full price history) for any city, ZIP or state; filter by price, beds, type and size. - **Market & pricing intelligence** — track list prices, price reductions, days-on-market signals (`isNewListing`, `isPriceReduced`, `isPending`) and inventory by area. - **Rental market research** — search for-rent inventory with monthly rents, beds/baths and amenities by neighborhood. - **Price-drop & new-listing alerts** — schedule the actor with **monitor mode** to emit only new listings, price drops/rises and status changes. ### How to use 1. [Sign up for Apify](https://console.apify.com/sign-up) — the free plan is enough to try this actor. 2. Open the **Realtor.com Scraper**, choose a **listing type** (for sale / for rent / sold), enter one or more **locations** (or paste Realtor.com search URLs), and click **Start**. 3. Watch results stream into the dataset table. 4. **Export** as JSON, CSV, Excel, XML or RSS — or pull results programmatically via the [Apify API](https://docs.apify.com/api/v2). ### Input ```json { "outputType": "search", "searchType": "for_sale", "location": ["Austin, TX", "78704"], "propertyTypes": ["house", "condo"], "priceMin": 300000, "priceMax": 900000, "bedsMin": 3, "sortBy": "newest", "includeAgentLeads": true, "maxResults": 200 } ```` - **outputType** — `search` (property listings), `agentLeads` (deduped agent/office contacts), or `propertyDetail` (full records by `property_id`). - **searchType** — `for_sale`, `for_rent`, or `sold` (recently sold comps). - **location** — one or more of `City, ST` (`Austin, TX`), a 5-digit ZIP (`78704`), a county, or a full state name (`Vermont`). Each is searched independently. - **searchUrls** — paste Realtor.com search pages directly: `realestateandhomes-search/...` (for sale), `apartments/...` (rent), `soldhomeprices/...` (sold). The listing type is taken from the URL. - **propertyTypes** — `house` / `single_family`, `condo`, `townhome`, `multi_family`, `duplex`, `mobile`, `land`, `farm`, `coop`. - **priceMin / priceMax / bedsMin / bedsMax / bathsMin / sqftMin / sqftMax** — filters (price is monthly rent for rentals). - **sortBy** — `relevant`, `newest`, `price_low`, `price_high`, `sqft`, `lot_size`, `sold_date`. - **includePropertyDetails** *(default false)* — also fetch each property's full record: complete feature list, assigned schools with ratings, full listing & price history, multi-year tax history and the photo gallery (billed as a property detail). - **includeAgentLeads** *(default false)* — also emit one deduped agent/office lead per listing agent. - **propertyIds** — numeric `property_id` values for `propertyDetail` mode. - **monitorMode / monitorKey** — only-new / changed output (see below). ### Output One record per property (`type: "property"`), plus optional `propertyDetail` and `agentLead` records: ```json { "type": "property", "propertyId": "7291872309", "listingId": "2997460536", "status": "for_sale", "listingType": "for_sale", "url": "https://www.realtor.com/realestateandhomes-detail/11910-Sunhillow-Bnd_Austin_TX_78758_M72918-72309", "price": 599900, "priceText": "$599,900", "beds": 6, "baths": 4, "sqft": 1936, "lotSqft": 7187, "propertyType": "multi_family", "yearBuilt": 1983, "line": "11910 Sunhillow Bnd", "city": "Austin", "state": "TX", "postalCode": "78758", "county": "Travis", "latitude": 30.398839, "longitude": -97.711, "listDate": "2026-06-12T03:35:54.000Z", "isNewListing": true, "mlsName": "AUTX", "mlsNumber": "4342289", "agentName": "Deep Parikh", "agentPhone": "(512) 659-4726", "officeName": "RealTech Realty, LLC", "photos": ["https://ap.rdcpix.com/...jpg"], "scrapedAt": "2026-06-23T17:12:35.503Z" } ``` Agent lead record (`type: "agentLead"`): ```json { "type": "agentLead", "agentId": "3147563", "name": "Deep Parikh", "email": "deep@real-tech.com", "phone": "(512) 659-4726", "website": "https://real-tech.com", "officeName": "RealTech Realty, LLC", "brokerName": "Real Broker, LLC", "sourceCity": "Austin", "sourceState": "TX", "listingsInRun": 3, "sampleListingUrl": "https://www.realtor.com/realestateandhomes-detail/...", "sampleListingPrice": 599900, "leadScore": 78, "scrapedAt": "2026-06-23T17:12:35.503Z" } ``` `propertyDetail` records add `features` (complete interior/exterior/utility list), `schools` (name, rating, distance), `priceHistory` (listed/sold/price-change events) and `taxHistory` (per-year tax + assessed value). ### Monitor mode — only new & changed Turn on **monitorMode** and the actor remembers what it emitted in previous runs (in a named key-value store) and outputs **only**: - **new** listings (or new agent leads), - **price\_drop** / **price\_rise**, - **status\_change** (e.g. for-sale → pending). Each record carries a `monitorReason`. This is built into the actor and works **independently of [Apify Schedules](https://docs.apify.com/platform/schedules)** — schedule the run as often as you like and only get the deltas. Use a distinct `monitorKey` per saved search so separate watch lists don't share state. ### Automate & schedule Run this actor on autopilot and pull results into your own stack: - **[Apify API](https://docs.apify.com/api/v2)** — start runs, fetch datasets, and manage schedules over REST. - **[apify-client for JavaScript](https://docs.apify.com/api/client/js/)** and **[apify-client for Python](https://docs.apify.com/api/client/python/)** — official SDKs. - **[Schedules](https://docs.apify.com/platform/schedules)** — run it hourly/daily to monitor new listings and price drops in a city, ZIP or for a saved search. - **[Webhooks](https://docs.apify.com/platform/integrations/webhooks)** — trigger downstream actions (CRM import, Slack alert, email sequence) the moment a run finishes. ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' }); const run = await client.actor('scrapesage/realtor-com-scraper').call({ outputType: 'search', searchType: 'for_sale', location: ['Austin, TX'], sortBy: 'newest', includeAgentLeads: true, maxResults: 200, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(`Got ${items.length} properties & agent leads`); ``` ### Integrate with any app Connect the dataset to 5,000+ apps — no code required: - **[Make](https://docs.apify.com/platform/integrations/make)** — multi-step automation scenarios. - **[Zapier](https://docs.apify.com/platform/integrations/zapier)** — push new agent leads straight into your CRM. - **[Slack](https://docs.apify.com/platform/integrations/slack)** — get notified when a monitored search finds new listings or price drops. - **[Google Drive / Sheets](https://docs.apify.com/platform/integrations/drive)** — auto-export every run to a spreadsheet. - **[Airbyte](https://docs.apify.com/platform/integrations/airbyte)** — pipe results into your data warehouse. - **[GitHub](https://docs.apify.com/platform/integrations/github)** — trigger runs from commits or releases. ### Use with AI assistants (MCP) The output is clean, LLM-ready JSON. You can call this actor from Claude, ChatGPT, or any agent framework through the **[Apify MCP server](https://docs.apify.com/platform/integrations/mcp)** — ask your assistant to "find new 3-bed homes under $700k in Austin and list the agents" and let it run this scraper for you. ### More scrapers from scrapesage Build a complete **real-estate + agent lead-gen stack**: - **[Redfin Scraper](https://apify.com/scrapesage/redfin-scraper)** — US for-sale & sold listings with prices and agent data. - **[Realtor.ca Scraper](https://apify.com/scrapesage/realtor-ca-scraper)** — Canadian listings and agent/brokerage leads. - **[Rent.com Scraper](https://apify.com/scrapesage/rent-com-scraper)** — US rental listings and property-management contacts. - **[Rightmove Scraper](https://apify.com/scrapesage/rightmove-scraper)** — UK property listings and agents. - **[Crexi Scraper](https://apify.com/scrapesage/crexi-scraper)** — US commercial real estate and broker leads. - **[FastExpert Scraper](https://apify.com/scrapesage/fastexpert-scraper)** — top real-estate agent profiles, reviews and leads. - **[Property Finder Scraper](https://apify.com/scrapesage/property-finder-scraper)** — UAE/GCC property listings and agent leads. - **[US Property Records Scraper](https://apify.com/scrapesage/us-property-records-scraper)** — public ownership & assessor records. - **[Website Contact Scraper](https://apify.com/scrapesage/website-contact-scraper)** — enrich any agent's website with emails, phones and socials. ### Tips - **Big states / cities**: Realtor.com paginates up to ~9,800 results per search. To exhaust a large area, split runs by ZIP, price band or property type. - **Cheapest rich run**: leave `includePropertyDetails` off — the listing record already carries price, beds/baths, sqft, geo, MLS, photos and the listing agent. Turn details on only when you need schools, full feature lists or price/tax history. - **Agent leads**: use the dedicated `agentLeads` mode to get one deduped, lead-scored record per agent across all matching listings (most-active agents first). - **Recurring monitoring**: combine [Schedules](https://docs.apify.com/platform/schedules) with `monitorMode` and `sortBy: "newest"` to capture only fresh inventory and price changes. ### FAQ **How do I scrape Realtor.com for a specific city?** Put the city in `location` as `City, ST` (e.g. `Austin, TX`), a ZIP, or a full state name. Combine with `searchType`, `propertyTypes` and the price/beds filters to narrow results. **Does it work without the Realtor.com API key?** Yes — there is no public Realtor.com API. This actor reads the same data Realtor.com's own website uses, no key or login needed. **Can I get sold-home comps?** Yes — set `searchType: "sold"` and `sortBy: "sold_date"`. Turn on `includePropertyDetails` for the full price history of each comp. **Where do the agent emails come from?** From the listing's own publicly displayed agent/office contact card on Realtor.com — the same details a visitor sees. Some agents publish only a phone or office email; fields are `null` only when the data doesn't exist. **Can I export to Google Sheets, CSV or Excel?** Yes — one click in the dataset view, or automatically on every run via the [Google Drive integration](https://docs.apify.com/platform/integrations/drive). **How do I monitor new listings or price drops automatically?** Turn on `monitorMode`, then create a [Schedule](https://docs.apify.com/platform/schedules). Each run emits only new/changed records, with a `monitorReason`. Add a [webhook](https://docs.apify.com/platform/integrations/webhooks) or [Zapier zap](https://docs.apify.com/platform/integrations/zapier) to push them into your CRM. **Is scraping Realtor.com legal?** This actor collects publicly available data only. You are responsible for using the data in compliance with applicable laws (e.g. GDPR/CCPA for personal data) and Realtor.com's terms. ### Need help? Open an issue on the actor's **Issues** tab, or visit the [Apify help center](https://help.apify.com/). Feature requests are welcome — this actor is actively maintained. # Actor input Schema ## `outputType` (type: `string`): search = property listings (the headline mode). agentLeads = deduped real-estate agent & office contact leads sourced from the matching listings. propertyDetail = full property records by numeric property\_id. ## `searchType` (type: `string`): Which market to search: homes for sale, rentals, or recently sold homes (great for comps & sold-price history). ## `location` (type: `array`): Where to search — one or more of: "City, ST" (e.g. "Austin, TX"), a 5-digit ZIP ("78704"), a county or a full state name ("Vermont"). Each location is searched independently. Leave empty if you use Search URLs. ## `searchUrls` (type: `array`): Paste Realtor.com search pages to scrape directly — for-sale (realestateandhomes-search/...), rentals (apartments/...) or sold (soldhomeprices/...). The listing type is taken from the URL. Works alongside the filters below. ## `propertyIds` (type: `array`): For outputType = propertyDetail: numeric Realtor.com property\_id values (the number you get back in the dataset, e.g. 8231543993). ## `propertyTypes` (type: `array`): Filter by property type. Accepts friendly names: house / single\_family, condo, townhome, multi\_family, duplex, mobile, land, farm, coop. Leave empty for all types. ## `priceMin` (type: `integer`): Only listings priced at or above this value. For rentals this is monthly rent. ## `priceMax` (type: `integer`): Only listings priced at or below this value. For rentals this is monthly rent. ## `bedsMin` (type: `integer`): Minimum number of bedrooms. ## `bedsMax` (type: `integer`): Maximum number of bedrooms. ## `bathsMin` (type: `integer`): Minimum number of bathrooms. ## `sqftMin` (type: `integer`): Minimum interior square footage. ## `sqftMax` (type: `integer`): Maximum interior square footage. ## `sortBy` (type: `string`): Result order. "newest" is ideal for monitoring fresh inventory; "sold\_date" for recent comps. ## `includePropertyDetails` (type: `boolean`): In search mode, fetch each property's full record (complete feature list, assigned schools with ratings, full listing & price history, multi-year tax history, photo gallery). Off = faster & cheaper (the listing record is already rich). When on, each record is billed as a property detail. ## `includeAgentLeads` (type: `boolean`): In search / propertyDetail mode, also emit one deduped agent/office lead per listing agent (name, email, phone, website, brokerage, lead score). The dedicated "Agent leads" mode outputs only leads. ## `maxPhotos` (type: `integer`): Cap on photo URLs collected per property in detail records. ## `maxResults` (type: `integer`): Overall cap on records (listings or leads) collected for this run. ## `monitorMode` (type: `boolean`): Remember what was emitted in previous runs (in a named key-value store) and output only NEW or CHANGED records — new listings, price drops/rises, status changes (and only-new agent leads). Each record carries a monitorReason. Perfect for scheduled deal-flow & price-watch alerts. Works independently of Apify Schedules. ## `monitorKey` (type: `string`): Namespace for monitor memory. Use a distinct key per saved search so separate watch lists don't share state. ## `maxConcurrency` (type: `integer`): Parallel requests. The actor rotates a fresh proxy IP per request; lower this if you hit throttling. ## `proxyConfiguration` (type: `object`): Proxy settings. Apify Proxy (datacenter) is recommended and enabled by default — Realtor.com's data API is clean from datacenter IPs with fresh-session rotation. ## Actor input object example ```json { "outputType": "search", "searchType": "for_sale", "location": [ "Austin, TX" ], "sortBy": "relevant", "includePropertyDetails": false, "includeAgentLeads": false, "maxPhotos": 25, "maxResults": 100, "monitorMode": false, "monitorKey": "default", "maxConcurrency": 5, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): All scraped property, property-detail and agent-lead records as JSON items in the default dataset. # 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 = { "location": [ "Austin, TX" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapesage/realtor-com-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 = { "location": ["Austin, TX"] } # Run the Actor and wait for it to finish run = client.actor("scrapesage/realtor-com-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 '{ "location": [ "Austin, TX" ] }' | apify call scrapesage/realtor-com-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesage/realtor-com-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Realtor.com Scraper - Properties, Prices & Agent Leads", "description": "Scrape Realtor.com for-sale, for-rent & sold listings — prices, beds/baths, sqft, photos, MLS, geo, schools, price & tax history — plus deduped real-estate agent & office leads with email, phone & website. Keyless, no browser. Filter by location, price & type; monitor new listings & price drops.", "version": "0.1", "x-build-id": "0BmrHpblihFI8gPrY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesage~realtor-com-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesage-realtor-com-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapesage~realtor-com-scraper/runs": { "post": { "operationId": "runs-sync-scrapesage-realtor-com-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapesage~realtor-com-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesage-realtor-com-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "outputType" ], "properties": { "outputType": { "title": "What to scrape", "enum": [ "search", "agentLeads", "propertyDetail" ], "type": "string", "description": "search = property listings (the headline mode). agentLeads = deduped real-estate agent & office contact leads sourced from the matching listings. propertyDetail = full property records by numeric property_id.", "default": "search" }, "searchType": { "title": "Listing type", "enum": [ "for_sale", "for_rent", "sold" ], "type": "string", "description": "Which market to search: homes for sale, rentals, or recently sold homes (great for comps & sold-price history).", "default": "for_sale" }, "location": { "title": "Locations", "type": "array", "description": "Where to search — one or more of: \"City, ST\" (e.g. \"Austin, TX\"), a 5-digit ZIP (\"78704\"), a county or a full state name (\"Vermont\"). Each location is searched independently. Leave empty if you use Search URLs.", "items": { "type": "string" } }, "searchUrls": { "title": "Search URLs (optional)", "type": "array", "description": "Paste Realtor.com search pages to scrape directly — for-sale (realestateandhomes-search/...), rentals (apartments/...) or sold (soldhomeprices/...). The listing type is taken from the URL. Works alongside the filters below.", "items": { "type": "string" } }, "propertyIds": { "title": "Property IDs (propertyDetail mode)", "type": "array", "description": "For outputType = propertyDetail: numeric Realtor.com property_id values (the number you get back in the dataset, e.g. 8231543993).", "items": { "type": "string" } }, "propertyTypes": { "title": "Property types", "type": "array", "description": "Filter by property type. Accepts friendly names: house / single_family, condo, townhome, multi_family, duplex, mobile, land, farm, coop. Leave empty for all types.", "items": { "type": "string" } }, "priceMin": { "title": "Price — min (USD)", "minimum": 0, "type": "integer", "description": "Only listings priced at or above this value. For rentals this is monthly rent." }, "priceMax": { "title": "Price — max (USD)", "minimum": 0, "type": "integer", "description": "Only listings priced at or below this value. For rentals this is monthly rent." }, "bedsMin": { "title": "Beds — min", "minimum": 0, "type": "integer", "description": "Minimum number of bedrooms." }, "bedsMax": { "title": "Beds — max", "minimum": 0, "type": "integer", "description": "Maximum number of bedrooms." }, "bathsMin": { "title": "Baths — min", "minimum": 0, "type": "integer", "description": "Minimum number of bathrooms." }, "sqftMin": { "title": "Square feet — min", "minimum": 0, "type": "integer", "description": "Minimum interior square footage." }, "sqftMax": { "title": "Square feet — max", "minimum": 0, "type": "integer", "description": "Maximum interior square footage." }, "sortBy": { "title": "Sort by", "enum": [ "relevant", "newest", "price_low", "price_high", "sqft", "lot_size", "sold_date" ], "type": "string", "description": "Result order. \"newest\" is ideal for monitoring fresh inventory; \"sold_date\" for recent comps.", "default": "relevant" }, "includePropertyDetails": { "title": "Include full property details", "type": "boolean", "description": "In search mode, fetch each property's full record (complete feature list, assigned schools with ratings, full listing & price history, multi-year tax history, photo gallery). Off = faster & cheaper (the listing record is already rich). When on, each record is billed as a property detail.", "default": false }, "includeAgentLeads": { "title": "Also output agent leads", "type": "boolean", "description": "In search / propertyDetail mode, also emit one deduped agent/office lead per listing agent (name, email, phone, website, brokerage, lead score). The dedicated \"Agent leads\" mode outputs only leads.", "default": false }, "maxPhotos": { "title": "Max photos per property", "minimum": 0, "maximum": 200, "type": "integer", "description": "Cap on photo URLs collected per property in detail records.", "default": 25 }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Overall cap on records (listings or leads) collected for this run.", "default": 100 }, "monitorMode": { "title": "Monitor mode (only new / changed)", "type": "boolean", "description": "Remember what was emitted in previous runs (in a named key-value store) and output only NEW or CHANGED records — new listings, price drops/rises, status changes (and only-new agent leads). Each record carries a monitorReason. Perfect for scheduled deal-flow & price-watch alerts. Works independently of Apify Schedules.", "default": false }, "monitorKey": { "title": "Monitor key", "type": "string", "description": "Namespace for monitor memory. Use a distinct key per saved search so separate watch lists don't share state.", "default": "default" }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 12, "type": "integer", "description": "Parallel requests. The actor rotates a fresh proxy IP per request; lower this if you hit throttling.", "default": 5 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings. Apify Proxy (datacenter) is recommended and enabled by default — Realtor.com's data API is clean from datacenter IPs with fresh-session rotation.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```