Realtor.com Scraper

What does Realtor.com Property Scraper do?

Realtor.com Property Scraper extracts property listings from any Realtor.com search page and delivers structured, ready-to-use data — no account, no API key, no code required. Paste a search URL and get back price, address, beds, baths, square footage, listing agent contacts, photos, and much more in seconds. Scrape up to 10,000 listings per search across the entire US market.

Need deeper data? Enable Get Property Details to also pull tax history, nearby school ratings, flood and noise risk scores, mortgage estimates, price history, HOA fees, open house schedules, and full photo galleries for every listing.

Output is available as JSON, CSV, or Excel — perfect for spreadsheets, CRM imports, or downstream data pipelines.

Why scrape Realtor.com data?

• Market research — track median prices, days on market, and price reduction trends across any zip code or city
• Investment analysis — combine list price, last sold price, estimated value, tax assessments, and HOA fees in a single dataset
• Lead generation — export listing agent names, phone numbers, and emails for every active listing in a target area
• Competitive intelligence — monitor new listings and price changes in a market by scheduling automatic daily or weekly runs
• Academic & journalistic research — build housing affordability datasets, school-district analyses, or neighborhood reports
• Portfolio tracking — pull detailed data for specific addresses to monitor value and listing status over time

How to scrape Realtor.com listings — step by step

1. Go to Realtor.com and run a property search in your target area.
2. Apply whatever filters you need — location, price range, beds, baths, property type.
3. Copy the URL from your browser's address bar.
4. Paste it into the Start URLs field in the Actor input.
5. Choose Get Property Details if you want the full data set, or leave it off for a faster lightweight run.
6. Click Save & Run. Results appear in the Output tab within seconds to minutes.

No technical setup needed. The Actor reads all filters directly from the URL.

Input

Field	Type	Default	Description
Start URLs	array	—	One or more Realtor.com search page URLs. Filters (beds, baths, price, type, sqft, keywords) are parsed automatically from the URL.
Full Scrape	boolean	false	Paginate through all available results until the end (up to ~10,000 per search). Uses a larger page size for efficiency. Overrides Max Items.
Get Property Details	boolean	false	Fetch the full listing detail page for every result: tax history, schools, flood risk, mortgage estimate, price history, and more. Slower but far richer.
CSV-Friendly Output	boolean	true	Flatten all fields to simple scalars with no nested objects — ideal for CSV and Excel. Disable to receive the full nested JSON structure.
Max Items	integer	100	Maximum listings to collect across all URLs. Set to 0 for unlimited. Ignored when Full Scrape is enabled.
Proxy Configuration	object	disabled	Optional proxy settings for high-volume or restricted runs.

Example input

{
  "startUrls": [
    { "url": "https://www.realtor.com/realestateandhomes-search/Austin_TX/type-single-family-home/price-300000-600000/beds-3" }
  ],
  "fullScrape": false,
  "getDetails": false,
  "csvFriendly": true,
  "maxItems": 500
}

You can add multiple URLs to scrape several markets in a single run.

Output

Search results (fast mode, getDetails: false)

Each row is fully flat — no nested objects, ready to open directly in Excel or import into a database:

{
  "property_id": "3948201234",
  "listing_id": "2981234567",
  "status": "for_sale",
  "url": "https://www.realtor.com/realestateandhomes-detail/123-Main-St_Austin_TX_78701",
  "list_date": "2026-04-15T14:00:00.000000Z",
  "last_update_date": "2026-05-01T09:30:00Z",
  "list_price": 449000,
  "price_per_sqft": 224,
  "price_reduced_amount": 10000,
  "last_sold_price": 312000,
  "last_sold_date": "2020-06-12",
  "hoa_fee": 75,
  "photo_url": "https://ap.rdcpix.com/example.jpg",
  "photo_count": 34,
  "is_new_listing": true,
  "is_price_reduced": true,
  "is_new_construction": false,
  "is_foreclosure": false,
  "beds": 3,
  "baths": 2,
  "sqft": 2005,
  "lot_sqft": 6534,
  "year_built": 2003,
  "property_type": "single_family",
  "garage": 2,
  "address": "123 Main St",
  "city": "Austin",
  "state_code": "TX",
  "postal_code": "78701",
  "latitude": 30.2672,
  "longitude": -97.7431
}

Full property details (getDetails: true)

Includes everything above plus:

{
  "pool": false,
  "fireplace": true,
  "stories": 1,
  "heating": "Central",
  "cooling": "Central Air",
  "property_styles": "Ranch",
  "description_text": "Beautiful 3/2 in a quiet cul-de-sac with updated kitchen...",
  "state": "Texas",
  "street_view_url": "https://maps.googleapis.com/...",
  "estimated_value": 461000,
  "mortgage_monthly_payment": 2389,
  "mortgage_loan_amount": 404100,
  "mortgage_down_payment": 44900,
  "agent_name": "Jane Smith",
  "agent_phone": "512-555-0101",
  "agent_email": "jane@brokeragefirm.com",
  "agent_state_license": "TX-12345",
  "office_name": "Austin Premier Realty",
  "office_phone": "512-555-0200",
  "mls_id": "1234567",
  "mls_name": "Austin MLS",
  "days_on_mls": 12,
  "photo_urls": ["https://ap.rdcpix.com/img1.jpg", "https://ap.rdcpix.com/img2.jpg"],
  "virtual_tour_url": "https://tours.example.com/123-main-st",
  "last_tax_year": 2024,
  "last_tax_amount": 8342,
  "last_assessed_total": 398000,
  "noise_score": 42,
  "flood_factor_score": 1,
  "flood_zone": "X",
  "features": "Interior: Hardwood Floors, Granite Counters; Exterior: Covered Patio, Sprinkler System",
  "schools": [
    { "name": "Travis Elementary", "rating": 8, "grades": "K-5", "funding_type": "public", "distance_miles": 0.4 },
    { "name": "O. Henry Middle", "rating": 7, "grades": "6-8", "funding_type": "public", "distance_miles": 0.9 }
  ],
  "open_houses": [
    { "start_date": "2026-05-11T13:00:00", "end_date": "2026-05-11T16:00:00", "methods": "In Person" }
  ],
  "property_history": [
    { "date": "2026-04-15", "event": "Listed", "price": 449000, "source": "Austin MLS" },
    { "date": "2020-06-12", "event": "Sold", "price": 312000, "source": "Public Record" }
  ],
  "building_permits": [
    { "project_name": "Kitchen Remodel", "type_of_work": "Alteration", "date": "2022-03-10", "status": "Final" }
  ]
}

You can download the dataset in JSON, CSV, Excel, or XML from the Output tab after the run completes.

Data fields reference

Fields marked D are only available when getDetails: true.

Field	Mode	Description
property_id	S+D	Unique Realtor.com property identifier
listing_id	S+D	Active listing identifier
listing_key	D	MLS listing key
status	S+D	for_sale or for_rent
url	S+D	Direct link to the listing page
application_url	D	Rental application URL
list_date	S+D	Date the listing was published
last_update_date	S+D	Date the listing was last updated
last_price_change_date	D	Date of the most recent price change
last_price_change_amount	D	Dollar amount of the most recent price change
coming_soon_date	D	Expected listing date for coming-soon properties
last_sold_date	S+D	Date of the previous sale
list_price	S+D	Current asking price
list_price_min / list_price_max	S+D	Price range (for multi-unit listings)
price_per_sqft	S+D	Price ÷ interior square footage
price_reduced_amount	S+D	Dollar amount of the most recent price cut
last_sold_price	S+D	Price of the previous sale
hoa_fee	S+D	Monthly HOA fee (0 if none)
estimated_value	D	Automated valuation estimate
mortgage_monthly_payment	D	Estimated monthly mortgage payment
mortgage_loan_amount	D	Estimated loan amount
mortgage_down_payment	D	Estimated down payment
beds	S+D	Number of bedrooms
beds_min / beds_max	D	Bedroom range (for multi-unit listings)
baths	S+D	Number of bathrooms
baths_consolidated	S+D	Combined baths as display string
baths_min / baths_max	D	Bathroom range (for multi-unit listings)
sqft	S+D	Interior square footage
sqft_min / sqft_max	D	Sqft range (for multi-unit listings)
lot_sqft	S+D	Lot size in square feet
year_built	S+D	Year of construction
garage	S+D	Number of garage spaces
garage_min / garage_max	D	Garage range (for multi-unit listings)
pool	D	Pool present
fireplace	D	Fireplace present
stories	D	Number of stories
heating	D	Heating system type(s)
cooling	D	Cooling system type(s)
property_type	S+D	Property type (single_family, condos, etc.)
property_sub_type	S	Property sub-type
property_styles	D	Architectural style(s)
property_name	S+D	Building or community name
description_text	D	Full listing description
address	S+D	Street address
city	S+D	City
state_code	S+D	Two-letter state code
state	D	Full state name
postal_code	S+D	ZIP code
latitude / longitude	S+D	GPS coordinates
street_view_url	D	Google Street View URL
is_new_listing	S+D	Listed within the past few days
is_pending	S+D	Under contract / pending
is_contingent	D	Sale is contingent
is_price_reduced	S+D	Price has been reduced
is_new_construction	S+D	Newly built property
is_foreclosure	S+D	Foreclosure property
is_coming_soon	D	Not yet active on MLS
is_deal_available	D	Special deal or incentive available
is_usda_eligible	D	Eligible for USDA loan
has_new_availability	S	New unit availability (rentals)
cats_allowed / dogs_allowed	D	Pet policy (rentals)
agent_name / agent_phone / agent_email	D	Primary listing agent contact
agent_url	D	Agent profile URL
agent_state_license	D	Agent license number
office_name / office_phone / office_email	D	Brokerage contact
office_url	D	Brokerage profile URL
mls_id / mls_name	D	MLS listing ID and source name
days_on_mls	D	Number of days on the MLS
feed_type	D	MLS feed type
listing_agent_name / listing_agent_phone / listing_agent_email	D	MLS source agent contact
listing_office_name	D	MLS source office name
photo_url	S+D	Primary listing photo
photo_count	S+D	Total number of photos
photo_urls	D	All listing photo URLs (array)
virtual_tour_url	D	3D or video tour link
last_tax_year / last_tax_amount	D	Most recent tax year and amount
last_assessed_building / last_assessed_land / last_assessed_total	D	Most recent assessed values
noise_score	D	Neighborhood noise level (0–100)
flood_factor_score / flood_zone	D	Flood risk score and FEMA zone
features	D	Full amenity and feature list as text
open_houses	D	Upcoming open house schedule (array)
schools	D	Nearby schools with name, rating, grades, distance (array)
property_history	D	Price and event history (array)
building_permits	D	Historical permit filings (array)

Tips and advanced options

• Filter in the URL first — use Realtor.com's own search filters before copying the URL. The Actor reads them automatically, so you only pay to scrape what you actually need.
• Multiple URLs in one run — add several city, zip-code, or filter-set URLs to scrape multiple markets simultaneously without running the Actor multiple times.
• Schedule for market monitoring — use the built-in Apify scheduler to re-run daily or weekly on the same URL and track price and availability changes over time.
• Raw JSON mode — turn off CSV-Friendly Output when ingesting data into a database or pipeline to receive the full nested structure without any field renaming or transformation.
• For-rent searches — paste any realtor.com/apartments/ URL to scrape rental listings with the same field set.

FAQ and support

Why are some fields empty? Not every listing has every field populated. New construction may lack tax history; some rentals omit school data; certain agents opt out of displaying contact information.

Why did the Actor stop before reaching my limit? Realtor.com limits search results to roughly 10,000 listings per query. For larger datasets, break the search into smaller sub-queries using tighter price ranges or specific zip codes.

Can I scrape a specific property address? The Actor works with Realtor.com search page URLs. To get data on a specific property, search for its address on Realtor.com, copy the resulting search URL, and run it with maxItems: 1 and getDetails: true.

Something not working or a feature request? Open an issue in the Issues tab on this Actor's page. Custom integrations, scheduled pipelines, or white-label solutions are available on request.

Contact

If you need a custom web scraping solution or have any questions, feel free to contact me or reach out via Discord. Let's discuss how I can help with your data needs!