Realtor.com Scraper

Realtor.com Scraper: US home listings by city, ZIP, county or a URL you paste

Type a location and every matching listing comes back as a row: address, price, beds, baths, square feet, lot size, property type, year built, status, days on market, the listing agent and broker, and the photos. For sale, for rent, recently sold, off market or ready to build.

The awkward part first. daysOnMarket counts from the list date on every row, whatever the status. On a sold or off-market listing that number keeps growing after the sale, so it is days since listing rather than days it was actually on the market. Use listDate and lastSoldDate when the difference matters.

🏷️ What Realtor.com Scraper does

Location takes Austin, TX, a five-digit ZIP, Travis County, TX, a neighbourhood like Zilker, Austin, TX, or a bare state code. One per line, and the whole run shares one budget and one duplicate check, so the same home found under two of your searches is delivered once.

Do not put a street address in there. It gets resolved to the area around it and searched as an area, so you would be billed for a neighbourhood's listings instead of the one house. Paste the property URL into Realtor.com URLs instead, which looks that one property up.

Pasted URLs keep their own filters. Price, beds, type and show-recently-sold written into a Realtor.com search URL are honoured, and search pages and single property pages both work.

Then there are the filters, and there are a lot of them: status, property type, price, beds, baths, living area, lot size, year built, how recently it was listed or sold, open houses, new builds, foreclosures, and keywords that have to appear in the listing.

One gotcha worth knowing: Realtor.com's own value is condos, plural. condo matches nothing.

📥 What you give it

{
  "location": ["Austin, TX"],
  "listingStatus": "for_sale",
  "propertyTypes": ["single_family"],
  "priceMax": 600000,
  "bedsMin": 3,
  "sortBy": "newest",
  "maxItems": 200
}

📤 What you get back

A real row from a run on 14 September 2026, with the feature list cut short:

{
  "propertyId": "9843409442",
  "listingId": "3000701603",
  "url": "https://www.realtor.com/realestateandhomes-detail/5009-Monarda-Mint-Dr_Austin_TX_78754_M98434-09442",
  "address": "5009 Monarda Mint Dr",
  "addressWithheld": false,
  "city": "Austin",
  "stateCode": "TX",
  "state": "Texas",
  "postalCode": "78754",
  "county": "Travis",
  "countyFips": "48453",
  "latitude": 30.367015769780284,
  "longitude": -97.62425231789224,
  "price": 490222,
  "pricePerSqft": 199,
  "priceReducedAmount": null,
  "lastSoldPrice": null,
  "lastSoldDate": null,
  "estimatedValue": null,
  "hoaFee": null,
  "beds": 4,
  "baths": 3,
  "bathsFull": 2,
  "bathsHalf": 1,
  "sqft": 2466,
  "lotSqft": null,
  "yearBuilt": null,
  "propertyType": "single_family",
  "stories": 2,
  "garage": 2,
  "listingStatus": "for_sale",
  "listDate": "2026-09-14T00:01:29.000000Z",
  "daysOnMarket": 0,
  "lastUpdateDate": "2026-09-14T00:01:29Z",
  "isNewListing": true,
  "isPending": false,
  "isForeclosure": false,
  "isNewConstruction": true,
  "agentName": "Cameron Place",
  "agentEmail": null,
  "brokerName": null,
  "brokerPhone": null,
  "mlsSourceId": "PULB",
  "mlsSourceType": "new_home",
  "photoCount": 1,
  "primaryPhoto": "http://nh.rdcpix.com/9c50d77ff4f6b0ce0b3c083f6a478599l-f1836003418s.jpg",
  "photos": ["http://nh.rdcpix.com/9c50d77ff4f6b0ce0b3c083f6a478599l-f1836003418s.jpg"],
  "virtualTourUrl": null,
  "hasMatterport": false,
  "openHouses": [],
  "features": ["new_construction", "two_or_more_stories", "garage_2_or_more", "kitchen_island", "..."],
  "searchLocation": "Austin, TX",
  "resolvedLocation": "Austin, TX",
  "position": 1,
  "scrapedAt": "2026-09-14T05:46:06.308Z"
}

🧾 Reading the output

Listing rows carry no charged field. The flag is only on the sample and diagnostic rows, to mark them as not real results.

A failure part way through paging keeps the rows already delivered and adds a diagnostic, so you can tell a short result from a complete one.

▶️ How to run it

1. Open Realtor.com Scraper and click Try for free. 2. Type a city, ZIP or county into Location, one per line. 3. Pick a Listing status and any filters you want under Filters. 4. Set Maximum listings. Start around 25 to see what the rows look like. 5. Click Start, then download the dataset as JSON, CSV or Excel, or read it from the Apify API.

💰 How much does it cost?

$0.68 per 1,000 listings. Flat on every Apify plan, with no volume tiers.

One billed row per listing delivered. The sample row is not billed, diagnostic rows are not billed, the same home found under two of your searches is billed once, and includePropertyDetails adds fields rather than rows so it does not change the price.

💡 What people use it for

• Comps and valuation work, pulling sold listings in one ZIP with soldWithinDays set.
• Agent and broker lead lists, grouped on brokerName across a metro.
• Watching new supply daily with listedWithinDays at 1, diffing on propertyId.
• Investment screens: foreclosure on, a price ceiling, and pricePerSqft to rank what comes back.
• Rental market snapshots by switching status to For rent and holding the rest of the filters.

🚧 What it does not do

• United States only. Realtor.com does not cover anywhere else.
• No more than 10,000 results per search. That is Realtor.com's paging depth, not ours. Split by

ZIP to go deeper, and watch for the RESULT_CAP row.

• daysOnMarket is days since listing on every status, so it keeps counting after a sale.
• No sale prices in non-disclosure states. lastSoldPrice is empty there because the number is

not public.

• Agent and broker emails are rarely published. Do not plan an email campaign around them.
• A street address in Location is treated as an area. Paste the property URL instead.
• A location lookup that fails comes back as not found. If you know the place exists, re-run

rather than concluding Realtor.com has never heard of it.

🧭 Which property scraper do you need?

❓ Questions people ask

How do I get recently sold homes? Set Listing status to Recently sold and use Sold within the last N days. Read lastSoldPrice and lastSoldDate, not daysOnMarket.

How do I get more than 10,000 listings for a city? Split the city into its ZIP codes and put them all in Location in one run. The duplicate check is shared, so overlapping areas cost once.

Can I look up one specific home? Yes. Paste its Realtor.com property URL into Realtor.com URLs.

Why did my condo filter return nothing? Realtor.com's value is condos, plural. Pick it from the list rather than typing it.

Can I schedule it? Yes. propertyId is stable, so diffing one run against the next shows what came on and what went under contract.

Is this legal? These are public listing pages. Agent names are personal data, so have a reason for collecting them. Apify's write-up on scraping and the law is a good starting point, and we are not lawyers.

🆘 If something breaks

Open the Issues tab on the actor page. Send the location or URL you used and the run ID. The errorCode on the diagnostic row usually names the problem on its own.