Realtor.com All-in-One Scraper

Listings, full property details, photos, agents, and addresses -- in one actor.

Point it at a city, a ZIP, or a Realtor.com search URL. The actor returns a clean, normalized dataset row for every property: address, geo coordinates, list price, beds, baths, living area, lot size, year built, property type, full-resolution photo URLs, and the listing agent's name, phone, and brokerage.

What it can do

• Search by URL or location -- supply a Realtor.com search-results URL, or a free-text location like "Austin, TX". The actor builds the right search URL automatically.
• Auto-pagination -- the actor walks every page of a search result up to the per-seed cap (default 50 pages). No "stopped at 40 listings" surprises on big metros.
• Full property details -- every listing is enriched with the full property page, not just the search-results summary. Address, photos, agent, and the rest are populated per row.
• High-resolution photos -- up to ~50 photo URLs per listing direct from Realtor's CDN, no auth required.
• Listing agent contact -- name, phone number, brokerage for every active listing.

Use cases

• Real-estate market analytics, comparable-sales modelling.
• Investor lead lists -- agents, brokerages, neighborhoods.
• Filtered home-search products, neighborhood inventory tracking.
• Cross-source unification with Zillow data (the dataset schema is identical to our Zillow All-in-One Scraper).

Why use this actor

• Production-tested on Apify cloud. The sample output below is real data from an actual run on Apify (run id BC23gG..., dataset DSCTabz6Va9rHeMHl).
• One run, complete data. Search + detail enrichment happen in the same pipeline. No second actor to wire up.
• Normalized schema. Unions cleanly with Zillow rows for portfolio-wide analytics.
• Fast. 5 listings emitted in ~6 seconds on the test run below; runs scale linearly with maxItems.

Sample input

{
  "locations": ["Austin, TX"],
  "status": ["for_sale"],
  "maxItems": 50,
  "maxConcurrency": 4,
  "maxRetries": 5,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Other ways to seed:

{ "searchUrls": [{ "url": "https://www.realtor.com/realestateandhomes-search/Austin_TX" }] }

{ "locations": ["94110", "Brooklyn, NY", "Austin, TX"], "maxItems": 200 }

Sample output (real data from a live Apify run)

Five real Austin TX listings emitted on 2026-05-14 from locations: ["Austin, TX"]:

{
  "source": "realtor",
  "sourceId": "9369011918",
  "url": "https://www.realtor.com/realestateandhomes-detail/4015-Margarita-St_Austin_TX_78723_M93690-11918",
  "address": {
    "line": "4015 Margarita St",
    "city": "Austin",
    "state": "TX",
    "zip": "78723",
    "lat": 30.292977,
    "lng": -97.6925
  },
  "status": "FOR_SALE",
  "price": 700000,
  "currency": "USD",
  "beds": 4,
  "baths": 3.5,
  "sqft": 2282,
  "lotSqft": 1512,
  "yearBuilt": 2022,
  "propertyType": "townhomes",
  "photos": [
    "https://ap.rdcpix.com/0f1732fda1bfb88b843986c6d7a49961l-m927859354s.jpg",
    "https://ap.rdcpix.com/0f1732fda1bfb88b843986c6d7a49961l-m1011188171s.jpg"
    /* ... 35 more photo URLs ... */
  ],
  "listingAgent": {
    "name": "Carolina Aceituno",
    "phone": "(512) 255-5050",
    "brokerage": "Keller Williams Realty -  Broker"
  },
  "priceHistory": [],
  "taxHistory": [],
  "scrapedAt": "2026-05-14T16:31:34Z"
}

Four more rows from the same run:

sourceId	Address	Price	Beds	Baths	sqft	Type	Year	Agent	Brokerage	Photos
9797030113	3524 Gonzales St Unit 2A, Austin 78702	$285,000	4	3.5	1925	townhomes	2025	Laura Ruiz	HomeBase	36
7686835844	11602 Maybach Dr, Del Valle 78617	$55,000	3	2	1331	single_family	1996	Dan O'Connell	Berkshire Hathaway HomeServices Texas Realty	1
9821033366	200 W 56th St Unit 8101, Austin 78751	$574,999	3	3	1525	multi_family	-	Koenig Townhomes	-	1
8861052094	7024 Thistle Hill Way, Austin 78754	$389,900	4	2.5	2788	single_family	1999	MARY MERRELL	Keller Williams Realty - Broker	40

Tips for best results

• Residential proxy recommended. Default is RESIDENTIAL / US -- keep it. Datacenter IPs work too on most runs but residential is more reliable for sustained crawls.
• Start small. First run with maxItems: 5 to confirm your input shape, then scale up.
• One location at a time for large cities. Pagination caps out around 50 pages per location seed -- if you need every listing in NYC or LA, feed multiple ZIP codes or neighborhood-level slugs in locations.
• Photos are CDN-direct. Each URL in photos is a stable ap.rdcpix.com URL you can store or hot-link.

Output dataset

Each row is pushed to the actor's default dataset as a flat JSON object matching the schema above. Export to CSV, JSON, JSONL, XML, or Excel from the Apify Console.

Notes & limits

• The actor scrapes only publicly visible data -- no login, no agent-only MLS fields, no off-market records.
• priceHistory and taxHistory fields are present in the schema but may be empty for some listings depending on what Realtor surfaces server-side for that property.
• Bounding-box inputs (boundingBoxes) are accepted for forward compatibility but currently ignored -- use locations or searchUrls for area-based scraping.
• For technical / architectural details, see the repo's root README.