🏑 Realtor.com Scraper β€” Property & Agents Β· $2/1k avatar

🏑 Realtor.com Scraper β€” Property & Agents Β· $2/1k

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🏑 Realtor.com Scraper β€” Property & Agents Β· $2/1k

🏑 Realtor.com Scraper β€” Property & Agents Β· $2/1k

Scrape Realtor.com for-sale and sold listings by city or zip: price, beds, baths, sqft, agent, office, MLS, coordinates and photos. No login, no API key. Use as an MCP server in Claude & AI agents.

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The Mine Works

The Mine Works

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🏑 Realtor.com Scraper β€” Property & Agent Data

What is the Realtor.com Scraper?

The Realtor.com Scraper extracts real estate listings from Realtor.com by city or ZIP code β€” returning clean, structured JSON for every for-sale and recently-sold property, with no login and no API key. Give it a location and get back price, beds, baths, square footage, price per sqft, listing agent, brokerage office, county, coordinates, and the listing URL. Every record carries the listing agent and office, making this ideal for real-estate lead lists.

Built lean and HTTP-only, it runs on Apify residential proxies and bills pay-per-result β€” the first 25 properties are free (lifetime), then just $2 per 1,000 results ($0.002 each).

Why scrape Realtor.com?

  • 🎯 Generate agent leads β€” every listing includes the agent name and brokerage office.
  • πŸ“ˆ Analyze the market β€” pull active and sold inventory to track price and supply trends.
  • 🏦 Source investment deals β€” filter by price and beds across an entire metro.
  • πŸ“Š Run comps & CMAs β€” combine for-sale and sold data for accurate valuations.
  • πŸ€– Feed AI & data products β€” deliver structured housing data straight into your pipeline.

Go beyond the limits of the official Realtor.com API

Realtor.com has no public listings API for developers β€” its data partnerships are gated, expensive, and coverage-limited. This actor talks directly to Realtor.com's own search backend over plain HTTP, so you are not capped by the row limits, rate limits, or licensing restrictions of a third-party feed. You choose the location, the filters, and the volume. No API key, no account, no unblocker subscription.

What data does the Realtor.com Scraper extract?

🏠 Full street addressπŸ’° List price
πŸ™οΈ City, state, ZIPπŸ—ΊοΈ County
πŸ›οΈ BedroomsπŸ› Bathrooms
πŸ“ Interior sqft🌳 Lot sqft
πŸ“ Price per sqftπŸ—οΈ Year built
🏑 Property type & sub-typeπŸ”– Listing status
πŸ’΅ Monthly HOA feeπŸ“… List date
🏷️ Last sold priceπŸ—“οΈ Last sold date
πŸ“ Latitude & longitudeπŸ“· Primary photo URL
πŸ‘€ Listing agent name🏒 Brokerage office name
πŸ”— Realtor.com listing URLπŸ†” Property & listing ID

How to scrape Realtor.com in 5 steps

  1. Create a free Apify account.
  2. Open the Realtor.com Scraper and enter a location (e.g. Austin, TX, 78704).
  3. Optionally set maxItems, soldMode, minPrice, maxPrice, or minBeds.
  4. Click Start and let the actor page through results.
  5. Download your data as JSON, CSV, or Excel, or pull it via the Apify API.

Example input

{
"location": "Austin, TX",
"maxItems": 100,
"soldMode": false,
"minPrice": 400000,
"minBeds": 3,
"proxyConfig": {
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "US"
}
}

To scrape recently-sold homes with sold price and date, set "soldMode": true.

Example output

Each property is returned as a flat JSON record:

{
"propertyId": "1234567890",
"listingId": "2987654321",
"status": "for_sale",
"address": "1234 Barton Springs Rd",
"city": "Austin",
"state": "TX",
"zip": "78704",
"county": "Travis",
"price": 749000,
"lastSoldPrice": null,
"lastSoldDate": null,
"beds": 3,
"baths": 2,
"sqft": 1720,
"lotSqft": 6098,
"yearBuilt": 2005,
"propertyType": "single_family",
"propertySubType": null,
"pricePerSqft": 435,
"hoaFee": null,
"listDate": "2026-06-28T00:00:00Z",
"latitude": 30.2621,
"longitude": -97.7712,
"photoCount": 34,
"photoUrl": "https://ap.rdcpix.com/abc123/1234567890-m0o.jpg",
"agentName": "John Doe",
"officeName": "Keller Williams Realty",
"url": "https://www.realtor.com/realestateandhomes-detail/1234-Barton-Springs-Rd_Austin_TX_78704_M12345-67890",
"scraped_at": "2026-07-10T18:20:44.301Z"
}

Field availability depends on what Realtor.com publishes for each listing; lastSoldPrice and lastSoldDate populate in recently-sold mode. Null fields are omitted from the record.

Use cases

  • Real-estate lead generation β€” extract agent and brokerage names for outreach and CRM.
  • Comparable sales & CMA β€” pull sold inventory in a ZIP to value a subject property.
  • Investor deal sourcing β€” filter by price band and beds to surface candidates across a metro.
  • Price & inventory monitoring β€” re-run on a schedule to track new listings and price changes.
  • Cross-portal enrichment β€” combine with Redfin and Zillow data for full market coverage.
  • AI real estate assistants β€” supply live listing data to LLM agents and valuation models.

FAQ

Do I need a Realtor.com account or API key?

No. The scraper requires no login, no cookies, and no API key. You only need an Apify account to run it.

Can I scrape recently-sold homes?

Yes. Set soldMode to true and the actor returns recently-sold homes with their last sold price and date instead of active for-sale listings.

How much does the Realtor.com Scraper cost?

Pay-per-result: the first 25 properties are free (lifetime), then $2 per 1,000 results ($0.002 per property). You only pay for properties actually returned.

How do I target a specific area?

Pass a ZIP code (78704) to narrow to one area, or a city with state (Austin, TX) for metro-wide results.

Scraping publicly available listing data is generally permissible, but results may include personal data (e.g. agent names) protected under laws like GDPR. Ensure you have a legitimate purpose and comply with applicable regulations.

Use in Claude, ChatGPT & any MCP agent

This actor is available as a hosted MCP server, so AI agents can call it directly:

https://mcp.apify.com/?tools=themineworks/realtor-scraper

Add that endpoint to Claude, ChatGPT, or any MCP-compatible client and ask it to pull Realtor.com listings on demand. Or call it from code with the Apify client:

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('themineworks/realtor-scraper').call({
location: 'Austin, TX',
maxItems: 100,
minBeds: 3,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Chain these siblings into a full property-data pipeline: