Realtor.com Property Scraper

Extract property listings from realtor.com, the largest US real estate listing site with over 100 million monthly visitors. Get comprehensive data including prices, property details, agent contacts, coordinates, photos, and more. Supports for sale, rental, and recently sold listings across all US markets.

What does Realtor.com Scraper do?

This Actor collects property listings from realtor.com for any US city or neighborhood. It extracts up to 200 listings per request and supports all listing types, property types, and search filters. Results are delivered in structured JSON format, ready for analysis or integration into your applications.

Key Features

Feature	Description
Search Any US Location	Enter a city and state to scrape properties in any market
All Listing Types	For Sale, For Rent, and Recently Sold properties
Property Type Filters	Single Family, Condo, Townhome, Multi Family, Mobile, Farm, Land
Price and Room Filters	Narrow results by price range, bedrooms, and bathrooms
200 Listings Per Page	High speed extraction with up to 200 properties per request
Rental Data	Building names, pet policies, individual unit details with prices
Sold Data	Sold price and sold date for recently sold listings
Agent and Brokerage Data	Contact details for listing agents and offices
Photos and Virtual Tours	Property images, 3D Matterport tours, and Google Street View links
GPS Coordinates	Latitude and longitude for mapping and geospatial analysis
MLS Data	MLS ID, MLS name, and source information
Resume Support	Checkpoint based resume for large scale scrapes

What data can you extract?

The scraper extracts 40+ fields per listing:

Property Details Property ID and listing URL Full address (street, city, state, zip, county) Latitude and longitude Property type (single family, condo, apartment, etc.) Bedrooms, bathrooms, sqft, lot sqft Year built and garage spaces Listing status and date	Pricing List price (for sale and sold) Price range min/max (rentals) Formatted display price Price reduced amount Sold price and sold date
Listing Flags New listing Price reduced Foreclosure New construction Pending / Contingent Coming soon Auction	Agent and Brokerage Agent name, email, phone Agent type (seller, management) Office and brokerage name MLS ID, MLS name, source type
Media and Location Up to 10 property photos (large format) Total photo count Virtual tour and 3D Matterport tour links Google Street View URL County FIPS code	Rental Specific Building and community name Pet policy (cats, dogs, small/large) Individual units with beds, baths, sqft, price, availability

How to use Realtor.com Scraper

Step 1: Choose your search mode

Search by Location (best for market research)

{
  "mode": "location",
  "locations": [
    { "city": "Portland", "state": "OR" },
    { "city": "Seattle", "state": "WA" }
  ],
  "listingType": "for_sale"
}

Direct URLs (best for specific searches with custom filters)

{
  "mode": "url",
  "urls": [
    "https://www.realtor.com/realestateandhomes-search/Portland_OR/type-single-family-home/beds-3",
    "https://www.realtor.com/apartments/Seattle_WA/beds-2"
  ]
}

Step 2: Add filters (optional)

{
  "mode": "location",
  "locations": [{ "city": "Denver", "state": "CO" }],
  "listingType": "for_sale",
  "propertyType": "single_family",
  "bedsMin": 3,
  "bathsMin": 2,
  "priceMin": 400000,
  "priceMax": 800000
}

Step 3: Scrape rentals

{
  "mode": "location",
  "locations": [{ "city": "Austin", "state": "TX" }],
  "listingType": "for_rent",
  "bedsMin": 2,
  "priceMin": 1000,
  "priceMax": 2500
}

Step 4: Scrape sold properties

{
  "mode": "location",
  "locations": [{ "city": "San Francisco", "state": "CA" }],
  "listingType": "sold",
  "propertyType": "condo"
}

Input Parameters

Parameter	Type	Default	Description
mode	string	location	Search mode: location or url
locations	object[]		Cities to search. Each has city (string) and state (2 letter code)
urls	string[]		Full realtor.com search URLs (for url mode)
listingType	string	for_sale	for_sale, for_rent, or sold
propertyType	string	any	any, single_family, condo, townhome, multi_family, mobile, farm, land
bedsMin	integer		Minimum bedrooms (1 to 5)
bathsMin	integer		Minimum bathrooms (1 to 5)
priceMin	integer		Minimum price (USD)
priceMax	integer		Maximum price (USD)
openHouseOnly	boolean	false	Only listings with open houses (for sale only)
newConstructionOnly	boolean	false	Only new construction (for sale and sold only)
maxListings	integer	20	Maximum total listings (0 = unlimited)
maxPages	integer	0	Maximum pages per location (0 = unlimited)
resumeFromCheckpoint	boolean	true	Resume from last checkpoint on restart
resumeFromRunId	string		Continue one interrupted run by pasting its run/dataset ID
incrementalMode	boolean	false	Track this search across scheduled runs and classify changes
stateKey	string		Optional manual key identifying the tracked baseline
emitUnchanged	boolean	false	Return (and bill) rows unchanged since the last run
emitExpired	boolean	false	Return (and bill) tombstone rows for listings no longer found

Filter Compatibility

Filter	For Sale	For Rent	Sold
propertyType	All types	All types	All types
bedsMin / bathsMin	Yes	Yes	Yes
priceMin / priceMax	Yes	Yes	Yes
openHouseOnly	Yes	Ignored	Ignored
newConstructionOnly	Yes	Ignored	Yes

Location Examples

City	State	What it searches
Portland	OR	All of Portland, Oregon
New York	NY	All of New York City
San Francisco	CA	San Francisco, California
Capitol Hill	WA	Capitol Hill neighborhood in Seattle
Orenco	OR	Orenco neighborhood in Hillsboro

Resume and recurring updates

Two related but distinct features:

• resumeFromRunId — continue ONE specific interrupted run. Paste a previous run ID or dataset ID from your account; listings it already collected are skipped so this run returns only the delta. This is different from resumeFromCheckpoint above, which auto-continues via this actor's own internal checkpoint (no ID needed), and from Incremental mode below (which tracks a recurring search on its own, without needing an ID at all).

• incrementalMode — turn this ON when you run this actor on a schedule against the same search. Each listing is classified against the previous run of the same search:

  • NEW — never seen before
  • UPDATED — seen before, one or more fields changed (changedFields lists which)
  • UNCHANGED — identical to the last run
  • REAPPEARED — was previously marked gone, is back
  • EXPIRED — a tombstone row for a listing no longer found, only emitted after a run that scanned every configured search to its natural end. A resume, a block, or a Max Pages/Max Listings cap skips EXPIRED detection for that run and keeps the previous state as-is, rather than risk marking still-live listings gone.

  Every dataset row also gets firstSeenAt / lastSeenAt timestamps. incrementalMode is OFF by default — existing scheduled runs are unaffected until you opt in.

  Which baseline a search is compared against is controlled by stateKey: leave it empty to auto-derive one from your location/URL and filter settings (two differently-configured searches never share a baseline either way), or set your own text to fully control it.

  Billing: a suppressed UNCHANGED row is never pushed, so it is never billed. emitUnchanged and emitExpired are both OFF by default for this reason — turning either on returns (and bills) extra dataset rows every run.

Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape — the Apify dataset is never changed.

What gets written to the connector: a condensed, human-readable summary of each record — not the full JSON. Each item becomes one entry with a title and its key fields flattened to plain text. The complete record always stays in the Apify dataset.

1. Authorize a connector once under Apify → Settings → Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "Pipe results into your apps" input field. (If the picker is empty, you haven't authorized a connector yet.)
3. For Notion, also set notionParentPageUrl to the page where items should be created.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

Output Example

For Sale

{
  "propertyId": "P100234567",
  "listingId": "L299887766",
  "url": "https://www.realtor.com/realestateandhomes-detail/123-Main-St_Portland_OR_97201_M12345-67890",
  "listingType": "for_sale",
  "status": "for_sale",
  "address": {
    "street": "123 Main St",
    "city": "Portland",
    "state": "Oregon",
    "stateCode": "OR",
    "postalCode": "97201",
    "county": "Multnomah",
    "full": "123 Main St, Portland, OR, 97201"
  },
  "coordinates": {
    "latitude": 45.5231,
    "longitude": -122.6765
  },
  "price": {
    "value": 525000,
    "display": "$525,000"
  },
  "features": {
    "propertyType": "single_family",
    "bedrooms": 3,
    "bathrooms": 2.5,
    "sqft": 1850,
    "lotSqft": 5200,
    "yearBuilt": 2005,
    "garage": 2
  },
  "flags": {
    "isNewListing": true
  },
  "agents": [
    {
      "name": "Jane Smith",
      "email": "jane@example.com",
      "type": "seller",
      "office": "Example Realty Group",
      "phone": "5035551234"
    }
  ],
  "brokerage": "Example Realty Group",
  "mlsId": "MLS12345",
  "mlsName": "RMLS",
  "streetViewUrl": "https://maps.googleapis.com/maps/api/streetview?...",
  "hasMatterport": true,
  "photos": [
    "https://ap.rdcpix.com/example-photo-od-w480_h360_x2.jpg"
  ],
  "photoCount": 32,
  "listDate": "2026-03-15T10:00:00.000000Z",
  "scrapedAt": "2026-03-23T10:30:00.000Z"
}

Rental

{
  "propertyId": "P960012345",
  "listingId": "L297700001",
  "url": "https://www.realtor.com/rentals/details/456-Oak-Ave_Portland_OR_97209_M96001-23456",
  "listingType": "for_rent",
  "status": "for_rent",
  "address": {
    "street": "456 Oak Ave",
    "city": "Portland",
    "stateCode": "OR",
    "postalCode": "97209",
    "county": "Multnomah",
    "full": "456 Oak Ave, Portland, OR, 97209"
  },
  "price": {
    "min": 1200,
    "max": 1800,
    "display": "$1,200 - $1,800"
  },
  "features": {
    "propertyType": "apartment",
    "bedrooms": 1,
    "bathrooms": 1,
    "sqft": 650
  },
  "buildingName": "Pearl District Apartments",
  "petPolicy": {
    "cats": true,
    "dogs": true
  },
  "units": [
    { "beds": 1, "baths": 1, "sqft": 650, "price": 1200 },
    { "beds": 2, "baths": 1, "sqft": 900, "price": 1800, "availableDate": "2026-04-01" }
  ],
  "scrapedAt": "2026-03-23T10:30:00.000Z"
}

Recently Sold

{
  "propertyId": "P121000001",
  "url": "https://www.realtor.com/realestateandhomes-detail/789-Elm-Dr_Portland_OR_97224_M12100-00001",
  "listingType": "sold",
  "status": "sold",
  "address": {
    "street": "789 Elm Dr",
    "city": "Portland",
    "state": "Oregon",
    "stateCode": "OR",
    "postalCode": "97224",
    "county": "Washington",
    "full": "789 Elm Dr, Portland, OR, 97224"
  },
  "price": {
    "value": 475000,
    "display": "$475,000"
  },
  "soldPrice": 465000,
  "soldDate": "2026-03-10",
  "features": {
    "propertyType": "single_family",
    "bedrooms": 3,
    "bathrooms": 2,
    "sqft": 1600,
    "yearBuilt": 1995
  },
  "brokerage": "Example Real Estate LLC",
  "mlsId": "MLS67890",
  "mlsName": "Willamette",
  "scrapedAt": "2026-03-23T10:30:00.000Z"
}