Realtor Detail Scraper | Property Details and Price History (2026)

From SilentFlow. Creators of Facebook Search Scraper and JD Products Scraper (#1 for “jd scraper” in Apify Store search), with 790,000+ combined lifetime runs.

The whole Realtor.com property page of every home on your list, one row per home: price, specs, listing agent and phone, county tax roll, price history, nearby schools, value estimates, mortgage estimate, flood and fire risk, and every photo in full size. Our default test run read 20 homes, from a condo for sale in Austin to a sold co-op in Manhattan, in 5 seconds.

Why choose this actor?

Opening Realtor.com tabs one address at a time to copy the price, the beds and the agent's phone? Getting 17 columns and a raw blob you still have to unpick before it fits a spreadsheet? Having to find every listing link before you can read a single home?

• 78 filled fields per home, not 17. On our default run (20 homes: 3 named one by one and the 17 newest listings in Austin, TX), 78 data fields were filled on at least half of the rows, as flat columns: MLS id and status, beds, baths, square feet, lot, year built, heating, cooling, parking, roof, parcel number, subdivision, school district, list price and price per square foot, estimated value with its range and source, annual tax, assessed value, HOA fee, monthly payment with its tax and insurance share, agent, office and broker contacts, flood factor, FEMA zone, fire factor, plus the tax roll (up to 18 years), the price history, the 7 to 12 nearest schools and every photo. The most used alternative announces 17 columns.
• Three ways in, in one run. Paste Realtor.com links (a home page, or a search page with its filters), type street addresses or areas (3808 Warm Meadows St, Las Vegas, NV, Austin, TX, 78704), or give property ids. One recently sold search page for ZIP 78704 gave 25 full homes in 4 seconds in our test. The most used alternative takes addresses and ids only.
• Nothing to fill before Start. No field is required: the form opens with a home link, an address, a property id and an area already in place, and returned 20 full homes as is. The most used alternative will not start without its list.

Try your first 20 homes

Paste this input in the JSON tab of the Input page and press Start. It reads a condo for sale in Austin from its link, a Las Vegas house from its street address, a Manhattan co-op from its property id, then the newest homes for sale in Austin, TX, up to 20 homes in all.

{
  "startUrls": [
    { "url": "https://www.realtor.com/realestateandhomes-detail/8800-White-Ibis-Dr-130_Austin_TX_78729_M92103-73898" }
  ],
  "searchQueries": [
    "3808 Warm Meadows St, Las Vegas, NV",
    "Austin, TX"
  ],
  "propertyIds": [
    "3291777140"
  ],
  "listingStatus": "for_sale",
  "maxItems": 20
}

It runs on the Apify Free plan. Each home becomes one row of your dataset: open the Output tab to see the table, switch to the "Value, tax and costs" or "Listing agents" view, or export the rows as JSON, CSV or Excel.

SilentFlow · Realtor suite
Realtor Rental Listings Scraper Realtor Rental Listings	Realtor Rental Scraper Realtor Rental Scraper	Realtor Detail Scraper You are here

Copy to your AI assistant

Paste this block into Claude, ChatGPT or Cursor to give it the full picture of this scraper:

You have access to the Realtor Detail Scraper on Apify: silentflow/realtor-detail-scraper

It reads the public property pages of US homes on Realtor.com (www.realtor.com), without an account,
and returns one row per home with everything the page shows.

Input schema (no field is required; give at least one link, address, area or property id):
- startUrls (array of {url}): Realtor.com home pages (/realestateandhomes-detail/..._M92103-73898,
  /rentals/details/...) give that home; search pages (/realestateandhomes-search/Austin_TX/beds-3/
  price-na-600000, /show-recently-sold, /show-pending, /apartments/Austin_TX) give their homes,
  newest first, with their filters.
- searchQueries (array of strings): a street address gives that home ("3808 Warm Meadows St, Las Vegas, NV");
  a city, ZIP code, neighborhood or county gives the newest homes listed there ("Austin, TX", "78704").
- propertyIds (array of strings): Realtor.com property ids ("3291777140", or "M92103-73898" as in a link).
- listingStatus (string, default "for_sale"): for_sale | pending | sold | for_rent. Applies to typed areas.
- maxItems (integer, default 50): homes saved in the whole run. Homes named one by one come first.

Output per home (98 fields, absent values are null, dates are RFC 3339 UTC):
- id (string, Realtor.com property id), url (string, permanent home page), status (for_sale, sold,
  off_market, for_rent...), listingId, mlsId, mlsName, mlsStatus (strings|null)
- propertyType, propertySubType (strings|null), beds, baths (numbers|null), bathsFull, bathsHalf, sqft,
  lotSqft, yearBuilt, stories, garageSpaces (integers|null), buildingName, builderName, description,
  heating, cooling, parking, flooring, laundry, constructionMaterials, roof, parcelNumber, subdivision,
  schoolDistrict (strings|null), features (array of {category, group, values[]}), tags (array of strings)
- listPrice, pricePerSqft, lastPriceChange, lastSoldPrice (integers|null, USD), lastPriceChangeDate,
  lastSoldDate (RFC 3339|null), estimatedValue, estimatedValueLow, estimatedValueHigh (integers|null),
  estimateSource (string|null), estimates (array of {value, low, high, date, source}), hoaFee (integer|null),
  hoaFeeFrequency (string|null), annualTax, assessedValue (integers|null), monthlyPayment, downPayment,
  loanAmount (integers|null), mortgageRate (number|null, percent), propertyTaxMonthly,
  homeInsuranceMonthly (integers|null), taxHistory (array of {year, tax, land, building, total}),
  priceHistory (array of {date, event, price, source}, newest first, up to 50)
- isNewListing, isPriceReduced, isForeclosure, isNewConstruction, isPending, isContingent, isComingSoon (booleans)
- address, unit, city, state, stateCode, postalCode, county, countyFips, neighborhood (strings|null),
  latitude, longitude (numbers|null), streetViewUrl (string|null), listDate, lastUpdateDate (RFC 3339|null),
  daysOnMarket (integer|null), openHouses (array of {start, end, description})
- agentName, agentEmail, agentPhone, officeName, officeEmail, officePhone, brokerName (strings|null)
- schools (array of {name, rating, distanceMiles, levels[], fundingType, grades[]}), floodFactorScore,
  fireFactorScore, noiseScore (integers|null), floodRisk, femaZone (strings|null)
- primaryPhoto (string|null), photos (array of full-size image URLs), photoCount (integer), virtualTourUrl (string|null)
- searchQuery (string, the link, address, area or id that gave the row), scrapedAt (RFC 3339)

Use apify-client for Python or JavaScript: client.actor("silentflow/realtor-detail-scraper").call(run_input=...).

How to scrape Realtor.com property details

Three inputs, from the simplest to the most complete. Each one runs as is.

Get the full page of one home from its link

Copy the link from your browser. Home pages for sale, sold, off market or for rent all work.

{
  "startUrls": [
    { "url": "https://www.realtor.com/realestateandhomes-detail/3808-Warm-Meadows-St_Las-Vegas_NV_89129_M18627-62703" }
  ]
}

Look up a list of street addresses

Type the addresses the way you would on Realtor.com. Each one gives its home, on or off the market, and the row keeps the address you typed in searchQuery so you can join it back to your list.

{
  "searchQueries": [
    "3808 Warm Meadows St, Las Vegas, NV",
    "13018 Lumberjack Rd NW Unit 1",
    "8800 White Ibis Dr Unit 130, Austin, TX"
  ],
  "maxItems": 50
}

Pull the recently sold homes of a ZIP code with their tax roll

Pick the listing status, type the ZIP code, set how many homes you want. The newest sales come first.

{
  "searchQueries": ["78704"],
  "listingStatus": "sold",
  "maxItems": 100
}

Input parameters

Parameter	Type	Default	What it does
startUrls	array of links	one home, prefilled	Realtor.com home pages give that home. Search pages give their homes, newest first, with the filters in the link.
searchQueries	array of text	an address and Austin, TX, prefilled	A street address gives that home. A city, ZIP code, neighborhood or county gives the newest homes listed there.
propertyIds	array of text	one id, prefilled	Realtor.com property ids, such as 3291777140, or M92103-73898 as written at the end of a link.
listingStatus	select	for_sale	Which homes a typed area gives: for_sale, pending, sold (recently sold) or for_rent.
maxItems	integer	50	Homes saved in the whole run, one row each.

No field is required. Mix the three kinds of input in one run: homes named one by one (links, ids, street addresses) are read first, then each area and search page fills the rest of maxItems with its newest homes. A home given twice, or found by both its link and its address, is saved once.

Accepted home links. https://www.realtor.com/realestateandhomes-detail/{address}_M{5 digits}-{5 digits} and https://www.realtor.com/rentals/details/{address}_M..., with or without ? parameters or a # anchor, with or without https://www..

Accepted search pages. https://www.realtor.com/realestateandhomes-search/{City}_{ST} or /{ZIP}, with the filters Realtor.com puts in the link: beds-3, baths-2, price-na-600000, sqft-800-na, type-single-family-home (also condo, townhome, multi-family-home, mfd-mobile-home, land, farms-ranches), and show-recently-sold or show-pending. Rental searches (/apartments/Austin_TX, /rentals/78701) work too. The page number of a pasted link is not kept: the run starts with the newest homes.

Addresses and areas. A street address starts with its number (3808 Warm Meadows St, Las Vegas, NV). Anything else is an area: a city with its state (Austin, TX), a ZIP code (78704), a neighborhood (Brooklyn Heights, Brooklyn, NY) or a county. An address Realtor.com does not know is reported in the log and gives no row; it never turns into a search of the whole city.

What data can you extract from Realtor.com?

One row per home, 98 fields, flat, ready for a spreadsheet, a CRM or a model. On our default run, 78 data fields were filled on at least half of the 20 rows.

Group	Fields
Identity (7)	id, url, status, listingId, mlsId, mlsName, mlsStatus
Home (26)	propertyType, propertySubType, beds, baths, bathsFull, bathsHalf, sqft, lotSqft, yearBuilt, stories, garageSpaces, buildingName, builderName, description, heating, cooling, parking, flooring, laundry, constructionMaterials, roof, parcelNumber, subdivision, schoolDistrict, features, tags
Price, value and costs (23)	listPrice, pricePerSqft, lastPriceChange, lastPriceChangeDate, lastSoldPrice, lastSoldDate, estimatedValue, estimatedValueLow, estimatedValueHigh, estimateSource, estimates, hoaFee, hoaFeeFrequency, annualTax, assessedValue, monthlyPayment, downPayment, loanAmount, mortgageRate, propertyTaxMonthly, homeInsuranceMonthly, taxHistory, priceHistory
Flags (7)	isNewListing, isPriceReduced, isForeclosure, isNewConstruction, isPending, isContingent, isComingSoon
Place and time (16)	address, unit, city, state, stateCode, postalCode, county, countyFips, neighborhood, latitude, longitude, streetViewUrl, listDate, lastUpdateDate, daysOnMarket, openHouses
Listing agent (7)	agentName, agentEmail, agentPhone, officeName, officeEmail, officePhone, brokerName
Neighborhood and risk (6)	schools, floodFactorScore, floodRisk, femaZone, fireFactorScore, noiseScore
Media (4)	primaryPhoto, photos, photoCount, virtualTourUrl
Run (2)	searchQuery, scrapedAt

The lists hold the detail behind the columns. taxHistory gives each year's tax with the land, building and total assessment (up to 18 years on our test rows). priceHistory gives every listing, price change, sale and removal, newest first, up to 50 events. estimates keeps each automated valuation with its source and date, and estimatedValue is the newest one. schools lists the nearest schools with their rating out of 10, distance in miles, levels and grades (7 to 12 per home in our tests). features keeps every block of the property page's feature list, such as "Interior Features", "Garage and Parking" or "Homeowners Association", with its values.

Usable as is. id is the Realtor.com property id: it stays the same across listings of the same home, so it is safe to deduplicate and join on across runs. url is the home's permanent page. Prices and taxes are whole US dollars, mortgageRate is a percentage (7.196), dates are RFC 3339 in UTC, and a value the page does not show is null, never an empty text or a 0. photos are the full-size images, not the small thumbnails of the search pages.

Output example

One home of the default run, a condo for sale in Austin, with the longer lists cut to their first entries:

{
  "id": "8338161764",
  "url": "https://www.realtor.com/realestateandhomes-detail/1807-Poquito-St-Apt-23_Austin_TX_78702_M83381-61764",
  "status": "for_sale",
  "listingId": "3002593819",
  "mlsId": "8308353",
  "mlsName": "UnlockMLS",
  "mlsStatus": "Active",
  "propertyType": "condos",
  "propertySubType": "condo",
  "beds": 2,
  "baths": 2,
  "bathsFull": 2,
  "bathsHalf": null,
  "sqft": 832,
  "lotSqft": 1263,
  "yearBuilt": 2008,
  "stories": 1,
  "garageSpaces": null,
  "buildingName": null,
  "builderName": null,
  "description": "Welcome to this charming 2-bedroom, 2-bath condo in the sought-after Willow Branch Lofts community, ideally located just minutes from the University of Texas. T...",
  "heating": "Central",
  "cooling": "Central Air",
  "parking": "Assigned, Electric Gate, Parking Lot, Private",
  "flooring": "Concrete, No Carpet",
  "laundry": "In Kitchen, Main Level",
  "constructionMaterials": "HardiPlank Type, Metal Siding",
  "roof": "Metal",
  "parcelNumber": "02090933050000",
  "subdivision": "Willow Branch Lofts",
  "schoolDistrict": "Austin ISD",
  "features": [
    {
      "category": "Appliances",
      "group": "Interior",
      "values": [
        "Dishwasher",
        "Electric Range",
        "Refrigerator",
        "Washer/Dryer"
      ]
    },
    {
      "category": "Bedrooms",
      "group": "Interior",
      "values": [
        "Bedrooms: 2",
        "Bedrooms On Main Level: 2",
        "Primary Bedroom Level: Main",
        "Bedroom 1 Level: Main"
      ]
    },
    {
      "category": "Bathrooms",
      "group": "Interior",
      "values": [
        "Total Bathrooms: 2",
        "Full Bathrooms: 2",
        "Primary Bathroom Level: Main",
        "Bathroom 1 Level: Main"
      ]
    }
  ],
  "tags": [
    "central_air",
    "central_heat",
    "community_security_features",
    "dishwasher",
    "washer_dryer",
    "single_story"
  ],
  "listPrice": 315000,
  "pricePerSqft": 379,
  "lastPriceChange": null,
  "lastPriceChangeDate": null,
  "lastSoldPrice": null,
  "lastSoldDate": "2017-07-19T00:00:00Z",
  "estimatedValue": 309427,
  "estimatedValueLow": 263012,
  "estimatedValueHigh": 355841,
  "estimateSource": "Quantarium",
  "estimates": [
    {
      "value": 310100,
      "low": 289100,
      "high": 331200,
      "date": "2026-10-05T00:00:00Z",
      "source": "Cotality™"
    },
    {
      "value": 326000,
      "low": 290100,
      "high": 361900,
      "date": "2026-10-14T00:00:00Z",
      "source": "Collateral Analytics"
    },
    {
      "value": 309427,
      "low": 263012,
      "high": 355841,
      "date": "2026-10-21T00:00:00Z",
      "source": "Quantarium"
    }
  ],
  "hoaFee": 204,
  "hoaFeeFrequency": "Monthly",
  "annualTax": 5385,
  "assessedValue": 263165,
  "monthlyPayment": 2534,
  "downPayment": 63000,
  "loanAmount": 252000,
  "mortgageRate": 7.196,
  "propertyTaxMonthly": 449,
  "homeInsuranceMonthly": 171,
  "taxHistory": [
    {
      "year": 2026,
      "tax": 5385,
      "land": 113768,
      "building": 149397,
      "total": 263165
    },
    {
      "year": 2025,
      "tax": 6096,
      "land": 113768,
      "building": 193842,
      "total": 307610
    },
    {
      "year": 2024,
      "tax": 5579,
      "land": 113768,
      "building": 218391,
      "total": 332159
    }
  ],
  "priceHistory": [
    {
      "date": "2026-10-29T00:00:00Z",
      "event": "Listed",
      "price": 315000,
      "source": "UnlockMLS"
    },
    {
      "date": "2017-07-19T00:00:00Z",
      "event": "Sold",
      "price": null,
      "source": "Public Record"
    }
  ],
  "isNewListing": true,
  "isPriceReduced": false,
  "isForeclosure": false,
  "isNewConstruction": false,
  "isPending": false,
  "isContingent": false,
  "isComingSoon": false,
  "address": "1807 Poquito St Apt 23",
  "unit": "Apt 23",
  "city": "Austin",
  "state": "Texas",
  "stateCode": "TX",
  "postalCode": "78702",
  "county": "Travis",
  "countyFips": "48453",
  "neighborhood": "Chestnut",
  "latitude": 30.279568,
  "longitude": -97.719686,
  "streetViewUrl": "https://maps.googleapis.com/maps/api/streetview?channel=rdc-streetview&location=1807%20Poquito%20St...",
  "listDate": "2026-10-29T02:16:02Z",
  "lastUpdateDate": "2026-10-29T02:08:09Z",
  "daysOnMarket": 0,
  "openHouses": [],
  "agentName": "Cole Reagan",
  "agentEmail": "cole.reagan@exprealty.com",
  "agentPhone": "5127202342",
  "officeName": "eXp Realty, LLC",
  "officeEmail": "linda.marcus@exprealty.com",
  "officePhone": "8885197431",
  "brokerName": "eXp Realty, LLC",
  "schools": [
    {
      "name": "Campbell Elementary School",
      "rating": 4,
      "distanceMiles": 0.4,
      "levels": [
        "elementary"
      ],
      "fundingType": "public",
      "grades": [
        "K",
        "1",
        "2",
        "3",
        "4",
        "5"
      ]
    },
    {
      "name": "Kealing Middle School",
      "rating": 9,
      "distanceMiles": 0.6,
      "levels": [
        "middle"
      ],
      "fundingType": "public",
      "grades": [
        "6",
        "7",
        "8"
      ]
    }
  ],
  "floodFactorScore": 1,
  "floodRisk": "minimal",
  "femaZone": "X (unshaded)",
  "fireFactorScore": 1,
  "noiseScore": null,
  "primaryPhoto": "https://ap.rdcpix.com/01db572659be34cb1f71ac36b1312414l-m3235934822od.jpg",
  "photos": [
    "https://ap.rdcpix.com/01db572659be34cb1f71ac36b1312414l-m3235934822od.jpg",
    "https://ap.rdcpix.com/01db572659be34cb1f71ac36b1312414l-m3973106621od.jpg",
    "https://ap.rdcpix.com/01db572659be34cb1f71ac36b1312414l-m3319035353od.jpg"
  ],
  "photoCount": 22,
  "virtualTourUrl": null,
  "searchQuery": "Austin, TX",
  "scrapedAt": "2026-10-29T03:52:16Z"
}

Advanced usage

Watch the new listings of a ZIP code every morning

Schedule this input daily on the Apify Schedules page. listDate, isNewListing and daysOnMarket tell the new homes apart, and id lets you drop the ones you already have.

{
  "searchQueries": ["78704"],
  "listingStatus": "for_sale",
  "maxItems": 100
}

Build sold comps for a valuation

Paste a Realtor.com sold search with the filters of the home you are pricing. Each comp comes with its sale date, last asking price, estimates, square feet, year built and tax roll.

{
  "startUrls": [
    { "url": "https://www.realtor.com/realestateandhomes-search/78704/type-single-family-home/beds-3/sqft-1500-2500/show-recently-sold" }
  ],
  "maxItems": 40
}

Enrich an address list from your CRM

Send the addresses from Python and write the columns you need back next to each one, using searchQuery to match them.

from apify_client import ApifyClient
import csv

client = ApifyClient("YOUR_APIFY_TOKEN")
addresses = ["3808 Warm Meadows St, Las Vegas, NV", "13018 Lumberjack Rd NW Unit 1"]
run = client.actor("silentflow/realtor-detail-scraper").call(
    run_input={"searchQueries": addresses, "maxItems": len(addresses)}
)
with open("enriched.csv", "w", newline="") as f:
    w = csv.writer(f)
    w.writerow(["address", "status", "beds", "baths", "sqft", "yearBuilt", "estimatedValue", "annualTax", "url"])
    for h in client.dataset(run["defaultDatasetId"]).iterate_items():
        w.writerow([h["searchQuery"], h["status"], h["beds"], h["baths"], h["sqft"],
                    h["yearBuilt"], h["estimatedValue"], h["annualTax"], h["url"]])

Reach the listing agents of pending homes in a neighborhood

Pending homes are the ones about to close: their listing agents know the street. Open the "Listing agents" view of the dataset for a ready call list with agent, phone, email and office.

{
  "searchQueries": ["Brooklyn Heights, Brooklyn, NY"],
  "listingStatus": "pending",
  "maxItems": 50
}

In our test, this area had 33 pending homes, and 10 of the 11 we read came with the agent's phone and email.

Screen a portfolio for flood and fire risk by property id

Give the ids of the homes you own, insure or lend on. Each row carries floodFactorScore (1 to 10), floodRisk, femaZone and fireFactorScore, next to the value estimate and the tax roll.

{
  "propertyIds": ["4933082940", "9210373898", "1862762703", "9248997688"],
  "maxItems": 4
}

FAQ

Do I need a Realtor.com account or an API key? No. The actor reads the property pages any visitor sees. No login, no key, nothing to set up before you press Start.

What is Realtor.com? Realtor.com is one of the largest US home listing sites, fed by the local MLS listing services. It keeps a page for most US homes, listed or not, with the listing, the public tax record, the sale history, schools and risk scores.

Which homes can I get? Any home Realtor.com has a page for: for sale, pending, recently sold, off market and for rent. Addresses and ids give their home whatever its status. Areas give the homes of the listingStatus you pick: in our test, Austin, TX had 6,701 homes for sale and ZIP 78704 had 6,061 recently sold homes.

Why is the sale price empty on some sold homes? Some states, Texas among them, do not make sale prices public, so Realtor.com does not show them. Those rows still carry the sale date, the last asking price, the price history and the estimated value. In our test, none of the 25 homes sold in ZIP 78704 (Austin) had a sale price, while the sold homes in Las Vegas and Manhattan did.

How does an address become a home? The run looks the address up the way Realtor.com's own search box does. If no home matches, the log says so and no row is saved: the run never swaps an unknown address for a search of the whole city. Writing the city and state after the street helps.

How many homes can I get per area? Up to maxItems for the whole run, newest first. There is no other limit: set the number you need and the run stops there. Homes named one by one are read before the areas, so a large area never pushes them out.

How fresh is the data? Live. Every run reads the pages at run time, nothing is cached. lastUpdateDate tells you when the listing itself last changed on Realtor.com.

Can I combine filters? Yes, through a search page link: beds-3/baths-2/price-na-600000/type-single-family-home/show-recently-sold returns recently sold single-family homes with 3 or more beds, 2 or more baths, priced up to 600,000 dollars. Build the search on Realtor.com, then paste its link.

Why are some fields empty on some homes? Each local listing service publishes its own set of facts. Heating, roof, parcel number or subdivision come from the listing and are often missing on homes that were never listed, on co-ops and on rentals. A value the page does not show is null. Rentals carry no mortgage estimate.

Are the photo links permanent? photos and primaryPhoto point to the full-size images on Realtor.com's image servers. Download the ones you need to keep long term.

Can I read thousands of homes in one run? Yes. Give as many links, addresses and ids as you have, or a large area, and set maxItems: the run saves homes as it goes, so the first rows are in your dataset within seconds.

Is it legal to scrape Realtor.com? The actor reads public pages only and never logs in. Agent names, emails and phone numbers are personal data: see the section below for how to handle them.

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• Pinterest - Pinterest Scraper
• Alibaba - Alibaba Products Scraper | Wholesale Prices and MOQ
• Eventim - Eventim Scraper | Events, Ticket Prices and Venues
• Leboncoin - Leboncoin Details Scraper | Full Ad Data and Sellers
• Udemy - Udemy Scraper
• Vinted Marketplace - Vinted Marketplace Scraper
• Agoda - Agoda Scraper | Hotel Prices and Guest Ratings
• Alibaba - Alibaba Scraper | Products, Supplier Companies and Prices
• AliExpress - AliExpress Reviews Scraper | Feedback, Ratings and Photos
• AliExpress - AliExpress Scraper | Products, Prices and Sales
• Avito - Avito Profiles Scraper | Sellers, Ratings and Reviews
• Back Market - Back Market Scraper | Refurbished Electronics Prices
• BAUHAUS - BAUHAUS Scraper | Product Prices, EAN and Specs
• CARFAX - CARFAX Scraper | Used Cars, Prices and History
• eBay Marketplace - eBay Marketplace Scraper
• Europages - Europages Scraper | Suppliers and B2B Companies
• Google Hotels - Google Hotels Scraper | Prices, Offers and Ratings
• Homedepot - Homedepot Reviews Scraper | Customer Reviews and Ratings
• Judge - Judge Scraper | Reviews, Ratings and Store Profiles
• Keepa - Keepa Scraper | Amazon Price History and Offers
• MakersRow - MakersRow Scraper | Manufacturers, Capabilities and Reviews
• Mercari - Mercari Scraper | Listings, Sold Prices and Sellers
• Sahibinden - Sahibinden Scraper | Real Estate and Car Listings
• Ticombo - Ticombo Scraper | Ticket Prices and Listings
• Trip - Trip Scraper | Hotels, Prices and Reviews
• Walmart - Walmart Scraper | Prices, Reviews, Sellers, Availability
• Webmotors - Webmotors Scraper | Car Listings, Prices and FIPE
• Woolworths - Woolworths Products Scraper | Prices, Specials and Nutrition
• Amazon - Amazon Product Scraper
• Amazon Marketplace - Amazon Marketplace Scraper
• AutoScout24 - AutoScout24 Scraper
• eBay Listings - eBay Listings Scraper
• Europages Deep Dive Extractor - Europages Deep Dive Extractor | VAT, Decision Makers, ISO Certs
• GasBuddy - GasBuddy Scraper | Gas Prices by Station
• Goofish - Goofish Detail Scraper | Listings, Prices and Sellers
• Mafengwo - Mafengwo Scraper | Attractions, Ratings and Tickets
• Vinted - Vinted Scraper
• Walmart - Walmart Product Scraper

💼 Jobs

• ZipRecruiter - ZipRecruiter Jobs Scraper | Salary, Company & Location Filters
• Indeed - Indeed Company Reviews Scraper
• Multi Board - Multi Board Job Scraper
• Jobright - Jobright Scraper | Jobs, Salaries and H1B Sponsors
• Malt Freelancer - Malt Freelancer Scraper
• Malt - Malt Scraper | Freelance Profiles
• Glassdoor - Glassdoor Jobs Scraper
• Glassdoor Job Listings - Glassdoor Job Listings Scraper
• Jora - Jora Jobs Scraper
• LinkedIn Job Search - LinkedIn Job Search Scraper | Salaries & Seniority
• ATS - ATS Jobs Scraper | Greenhouse, Lever and Ashby
• 🔥 Glassdoor - 🔥 Glassdoor Scraper
• Dice - Dice Jobs Scraper | US Tech Jobs, Salaries, Skills
• Dice Tech - Dice Tech Jobs Scraper
• iimjobs - iimjobs Jobs Scraper | MBA, Finance and Hirist Tech Jobs
• Instahyre - Instahyre Jobs Scraper | Companies, Recruiters and Ratings
• Jora - Jora Scraper | Jobs in Australia, New Zealand, Singapore
• StepStone - StepStone Scraper
• Welcome to the Jungle - Welcome to the Jungle Job Scraper
• YCombinator - YCombinator Jobs Scraper | Startup Jobs, Salaries and Founders
• All - All Jobs Scraper
• Arbeitsagentur - Arbeitsagentur Scraper | German and Austrian Job Board
• Arbeitsagentur - Arbeitsagentur Jobs Scraper
• Cutshort - Cutshort Jobs Scraper | Salaries, Skills and Companies
• iimjobs - iimjobs Scraper | Jobs, Companies and Recruiters
• Indeed - Indeed Companies Scraper | Reviews, Salaries, Interviews
• Indeed - Indeed Jobs Scraper | NLP Skills
• Indeed - Indeed Jobs Scraper | Job Listings in 73 Countries
• LinkedIn - LinkedIn Jobs Scraper
• Naukri & NaukriGulf - Naukri & NaukriGulf Jobs Scraper
• Seek - Seek Job Scraper
• Welcome to the Jungle - Welcome to the Jungle Scraper | Jobs and Company Data
• Ziprecruiter - Ziprecruiter Scraper

🏠 Real estate

• SeLoger - SeLoger Scraper | Real Estate Listings
• Airbnb Professional Host - Airbnb Professional Host Scraper | Emails, Phones, SIRET
• Airbnb Pro Host Contact & - Airbnb Pro Host Contact & Email Scraper
• Bien'ici - Bien'ici Scraper | Property Listings
• Rightmove - Rightmove Scraper
• SeLoger - SeLoger Scraper | French Property Listings and Agencies
• Trulia Rental Listings - Trulia Rental Listings Scraper
• Idealista - Idealista Scraper
• Airbnb Search - Airbnb Search Scraper
• Bienici - Bienici Scraper
• Realestate.com.au - Realestate.com.au Scraper
• Zapimoveis - Zapimoveis Scraper | Real Estate Listings and Prices
• Zillow - Zillow Scraper
• Airbnb Search - Airbnb Search Scraper | Prices, Fees, Amenities, Hosts
• Anjuke - Anjuke Scraper | Rental Listings, Prices and Agents
• Idealista - Idealista Scraper
• Trulia Rental - Trulia Rental Scraper | US Rentals, Prices, Pet Policy

📣 Social media

• LinkedIn Post Search - LinkedIn Post Search Scraper | Keywords, Hashtags & Profiles
• Facebook Search - Facebook Search Scraper
• Instagram - Instagram Story Scraper | Stories & Highlights
• LinkedIn Leads - LinkedIn Leads Scraper | Sales Navigator Export
• Facebook Search - Facebook Search Profiles Scraper | People by Name or Keyword
• TikTok Trend - TikTok Trend Scraper | Trending Hashtags and Videos
• YouTube - YouTube Channel Scraper | Videos, Shorts and Views
• TikTok - TikTok Scraper
• LinkedIn Sales Navigator - LinkedIn Sales Navigator Scraper
• Pinterest - Pinterest Ads Scraper | Ad Library, Reach & Targeting
• Reddit - Reddit Scraper | Posts, Comments and Subreddits
• Snapchat - Snapchat Videos Scraper | Spotlight Videos, MP4 and Stats
• TikTok Creative - TikTok Creative Ads Scraper | Top Ads, Landing Pages & Metrics
• Discord - Discord Scraper | Servers, Member Counts and Invites
• Kwai - Kwai Scraper | Videos, Creators and Hashtags
• Likee - Likee Scraper | Videos, Hashtags and Creators
• LinkedIn Event - LinkedIn Event Scraper
• LinkedIn Hashtag & - LinkedIn Hashtag & Post Scraper | No Cookies
• Meta Ad Library - Meta Ad Library Scraper
• Bandsintown - Bandsintown Scraper | Concerts and Tour Dates
• Discord - Discord Profiles Scraper | Users, Badges and Server Tags
• Facebook Thread - Facebook Thread Profiles Scraper | Followers, Bios & Engagement
• Instagram Engagement - Instagram Engagement Scraper
• Kuaishou - Kuaishou Scraper | Videos, Comments and Creator Stats
• LinkedIn Ads Library - No Cookies - LinkedIn Ads Library Scraper - No Cookies
• OnlyFans - OnlyFans Profile Scraper
• Pinterest - Pinterest Profiles Scraper | Followers, Emails and Bios
• Pinterest - Pinterest Videos Scraper | Video Downloader, MP4 Links, Stats
• Reddit - Reddit Comments Scraper | Search, Threads and Replies
• Reddit - Reddit Profiles Scraper | User Karma, Activity and Communities
• RedNote - RedNote Videos Scraper | Downloader, Transcripts and Stats
• Snapchat - Snapchat Contacts Scraper | Phones, Emails and Websites
• TikTok Lookalike - TikTok Lookalike Scraper | Influencers, Emails and Engagement
• TwitchTracker - TwitchTracker Scraper | Twitch Streamer Stats and Rankings
• X Timeline - X Timeline Scraper | Tweets and Engagement Stats
• Xigua - Xigua Scraper | Videos, Creators and Downloads
• YouTube Autocomplete - YouTube Autocomplete Scraper | Keyword Suggestions
• Douyin - Douyin Comments Scraper | Comments, Likes and IP Regions
• Facebook - Facebook Company Scraper | Emails, Phones, Ratings
• Facebook Business Page - Facebook Business Page Scraper
• OnlyFans - OnlyFans Creator Scraper
• Reddit - Reddit Scraper | Comments, Posts and Users
• RedNote - RedNote Detail Scraper | Xiaohongshu Details, Images, Videos
• Skool Group - Skool Group Scraper
• Skool Community - Skool Community Scraper
• Snapchat - Snapchat Ads Scraper | Ad Library, Impressions & Targeting
• Weibo - Weibo Scraper | Posts, Profiles and Engagement
• YouTube - YouTube Transcript Scraper

🏢 Business data

• Tencent - Tencent Scraper | Maps Places, Phones and Ratings
• LinkedIn Company Search - LinkedIn Company Search Scraper | Profiles & Firmographics
• Ctrip - Ctrip Scraper | Attractions, Tickets and Reviews
• LinkedIn People Search - LinkedIn People Search Scraper | Profiles & Companies
• 2GIS - 2GIS Reviews Scraper | Ratings, Photos and Owner Replies
• Bilibili - Bilibili Scraper | Videos, Profiles, Comments, Danmaku
• Teachable Course - Teachable Course Scraper
• Website Tech Stack - Website Tech Stack Scraper
• Teachable - Courses, Prices & Instructors - Teachable Scraper - Courses, Prices & Instructors
• Trustpilot - Trustpilot Scraper | Reviews, Ratings and Company Contacts

✈️ Travel

• Flight Price - Flight Price Scraper
• Booking.com Hotel - Booking.com Hotel Scraper
• Despegar - Despegar Reviews Scraper | Hotel Reviews and Ratings
• Google Maps - Google Maps Scraper
• Kakao - Kakao Scraper | Map Places, Reviews and Phones
• OpenTable - OpenTable Reviews Scraper | Restaurant Reviews and Ratings
• TheFork - TheFork Scraper | Restaurants, Menus and Ratings
• Zomato - Zomato Reviews Scraper | Restaurant Ratings and Replies
• Booking - Booking Scraper | Hotel Prices, Photos, Availability
• Trip - Trip Reviews Scraper | Hotel Reviews and Ratings

🎯 Lead generation

• Northdata - Northdata Company Scraper
• Dealroom - Dealroom Scraper | Companies and Investors
• ZocDoc - ZocDoc Scraper | Doctors, Reviews and Availability
• UK Companies House - UK Companies House Enricher
• BuiltWith - BuiltWith Scraper | Tech Stacks and Top Sites
• CNPJ Brazilian - CNPJ Brazilian Company Enricher
• Justdial - Justdial Companies Scraper | Business Leads, Phones and Emails
• PagesJaunes - PagesJaunes Scraper | French Business Emails and SIRET
• SIRET - SIRET Company Enricher
• Company Data - Company Data Scraper | Emails, Phones and Tech Stack
• Dealroom Startup Data - Dealroom Startup Data Scraper
• Delaware - Delaware Scraper | Corporations, LLCs and Registered Agents
• French Company Prospector - French Company Prospector
• KVK - KVK Scraper | Dutch Companies and SBI Codes
• PagesJaunes - PagesJaunes Business Scraper
• Pappers - Pappers Scraper | French Companies, Directors & Financials
• SEC - SEC Scraper | EDGAR Filings and Company Data
• SoftwareAdvice - SoftwareAdvice Scraper | Reviews, Ratings and Pros & Cons
• Sunbiz - Sunbiz Companies Scraper | New Florida Business Leads
• Sunbiz - Sunbiz Scraper | Florida Companies and Officers
• USPTO - USPTO Scraper | Trademark Search and Status
• Clutch - Clutch Scraper | Agencies, Reviews, Ratings, Services
• Clutch Agency - Clutch Agency Scraper
• Domain - Domain Enricher
• G2 - G2 Reviews Scraper
• Google Ads Transparency - Google Ads Transparency Scraper
• SIRET French - SIRET French Company Enricher
• ThomasNet Suppliers - ThomasNet Suppliers Scraper
• ZocDoc - ZocDoc Scraper

🔎 SEO

• Similarweb - Similarweb Scraper | Website Traffic, Rankings and Competitors
• Scribd - Scribd Scraper | Documents, Authors and Views
• SpyFu - SpyFu Scraper | SEO, PPC and Competitor Data
• Apple - Apple Reviews Scraper | App Store Reviews and Ratings
• Apple - Apple Scraper | App Store Apps, Ratings and Charts
• Bing - Bing Enricher Scraper | Mobile Friendly Test and Indexing
• Google News - Google News Scraper

📈 Marketing

• Douyin - Douyin Transcript Scraper | Subtitles and Speech to Text

🎬 Video

• Pexels - Pexels Scraper | Photos, Videos and Download Stats

📰 News

• ForexFactory - ForexFactory Scraper | Economic Calendar and Forecasts

🧰 More tools

• Maersk - Maersk Scraper | Vessel Schedules and Port Calls
• FanDuel - FanDuel Scraper | Odds, Spreads and Player Props
• PrizePicks - PrizePicks Scraper | Player Props, Lines and Projections

Support

Need something this scraper does not do yet? We ship features fast.

• Feature requests go straight to our backlog
• Enterprise needs? We do custom integrations and high-volume plans
• Pricing questions? Check the Monetization tab on the actor page

Response time: usually under 24 hours.

Legal compliance

This actor extracts publicly available property data from Realtor.com. It does not log in and does not bypass any login, paywall or CAPTCHA. Users are responsible for complying with Realtor.com's terms of service and with the data protection laws that apply to them (GDPR in the EU, CCPA in California, PIPL in China). Listing agent names, emails and phone numbers are personal data: store them only for a legitimate purpose, keep them no longer than needed, and respect do-not-call and anti-spam rules before contacting anyone. Estimates, tax figures and risk scores are informational: verify them before any lending, insurance or valuation decision.

Realtor Detail Scraper by SilentFlow: the whole property page of every home, one row each.