US Real Estate

Extract comprehensive property listings across the entire US — pricing, specs, agent contacts, valuations, MLS data, photos, and open houses.

Search by ZIP code, city, state, full address, neighborhood, or county. Get up to 10,000 properties per run with 50+ data fields covering sales, rentals, sold, pending, and off-market listings.

🤝 Support & Community

📧 Support: Contact Us 💬 Community: Telegram Group

🏆 Key Features

🏠 Flexible Location Search

• 📍 Any US Location: Search by ZIP code (10001), city (Austin), city + state (Austin, TX), full address (350 5th Ave, New York, NY 10118), neighborhood (South Beach), county (Cook County), or entire state (Texas).
• 🗺️ Full Coverage: Access property data across all 50 states, including rural areas, suburbs, and metro markets.
• 🔎 7 Listing Types: Query for sale, for rent, sold, pending, off-market, new community, or ready-to-build properties — one type per run.

💰 Complete Pricing & Valuation Data

• 💵 List & Sold Prices: Current asking price, final sold price, price range for negotiable listings, and price per square foot.
• 📊 Automated Valuations: Best estimated value with high/low range from automated valuation models (AVM).
• 🏦 HOA Fees: Monthly homeowners association fees when applicable.

📋 Rich Property Details

• 🛏️ Full Specs: Bedrooms, full/half bathrooms, living area (sqft), lot size, year built, garage spaces, stories, and property type.
• 🏷️ Status Flags: New construction, contingent, and pending indicators with exact status change dates.
• 📸 Media: Primary photo, full photo gallery URLs, and scheduled open house events with date/time windows.
• 📝 Descriptions & Tags: Full marketing description text and amenity/feature tags from each listing.

👤 Agent & Broker Information

• 🤝 Seller Agent: Name, email, phone, office name, and managing broker details.
• 👥 Co-Listing Agent: Secondary agent name and phone when available.
• 🏢 MLS Data: MLS board ID, MLS listing ID, and exact MLS status for cross-referencing.

📍 Geographic & Tax Data

• 🌐 Coordinates: Latitude/longitude (WGS 84) for mapping and geospatial analysis.
• 🏘️ Neighborhoods: Associated subdivision and neighborhood names.
• 📄 Tax Records: Public tax record ID and FIPS county code for data analysis.
• 🐾 Pet Policy: Dog and cat permission flags for rental properties.

💰 Pricing

Resource	Cost	Description
Actor Usage	$0.00001	Charged for Actor compute and storage. Cost depends on resource consumption during execution
Property	$0.00189	Per property returned — price, address, status, and listing details.

Example Cost Calculation:

• Searching Austin, TX for sale, 500 properties
• Cost: 500 × $0.00189 = $0.95 + minimal runtime fees

🌟 Why choose this Actor?

Purpose-built for US real estate data extraction, this Actor delivers comprehensive property listings with pricing, valuations, agent contacts, and MLS data in a single API call.

Feature	US Real Estate	Bright Data	ScraperAPI	Zyte
Pricing Model	✅ $0.00189/property	❌ $500+/month	❌ $49+/month	❌ Enterprise only
Data Fields	✅ 50+ per property	⚠️ Limited	⚠️ Limited	⚠️ Varies
No Commitment	✅ Pay-per-result	❌ Monthly contract	❌ Monthly contract	❌ Annual contract
Listing Types	✅ 7 types supported	⚠️ Sales only	⚠️ Limited	❌ Basic
Valuation Estimates	✅ AVM included	❌ No	❌ No	❌ No
Agent Contacts	✅ Email + Phone	⚠️ Name only	❌ No	❌ No
Setup Complexity	✅ No-code, 1-click	⚠️ Technical setup	⚠️ API integration	❌ Complex setup

💻 Input Parameters

Parameter	Type	Required	Description
location	string	✅ Yes	US location: ZIP code, city, city+state, full address, neighborhood, county, or state
max_results	integer	✅ Yes	Maximum properties to return (100–10,000)
listing_type	string	✅ Yes	One listing status to search: for_sale, for_rent, sold, pending, off_market, new_community, ready_to_build
property_type	string[]	❌ No	Filter by property style: single_family, multi_family, condos, townhomes, land, etc.
listed_since	string	❌ No	Time filter: relative ("7 days", "1 year") or absolute date ("2025-06-15")

📝 Example Input

{
  "location": "Austin, TX",
  "max_results": 500,
  "listing_type": "for_sale",
  "property_type": ["single_family", "condos"],
  "listed_since": "6 months"
}

📤 Output Structure

Field	Type	Description
processor	string	URL of the Apify actor that processed this data
processed_at	string	ISO 8601 timestamp when the data was processed
property_url	string	Full URL to the property listing page
property_id	string	Unique property identifier
listing_id	string	Unique listing identifier for this listing event
mls_id	string	MLS board identifier code (e.g. SDCA, CRMLS)
mls_listing_id	string	Listing ID within the MLS board
status	string	Listing status: for_sale, for_rent, sold, pending, etc.
mls_status	string	Exact MLS status string from the listing board
is_new_construction	boolean	True if the property is newly built
is_contingent	boolean	True if under contract with contingencies
is_pending	boolean	True if under contract pending closing
date_listed	string	Date the property was first listed
date_pending	string	Date the listing entered pending status
date_sold	string	Date the property sale was closed
date_updated	string	Date the listing was last modified
date_status_changed	string	Date and time the listing status last changed
list_price	number	Current asking price in USD
list_price_min	number	Minimum asking price for range-priced listings
list_price_max	number	Maximum asking price for range-priced listings
sold_price	number	Final recorded sale price in USD
price_per_sqft	number	Price per square foot in USD
hoa_fee	number	Monthly HOA fee in USD
estimated_value	number	Best automated valuation estimate in USD
estimated_high	number	Upper bound of valuation range in USD
estimated_low	number	Lower bound of valuation range in USD
property_type	string	Property style: single_family, condos, land, etc.
beds	integer	Number of bedrooms
baths_full	integer	Number of full bathrooms
baths_half	integer	Number of half bathrooms
sqft	integer	Interior living area in square feet
lot_sqft	integer	Total lot area in square feet
year_built	integer	Year the structure was built
garage_spaces	integer	Number of garage parking spaces
stories	integer	Number of above-ground floors
address	string	Street address line
unit	string	Apartment or unit number
city	string	City name
state	string	Two-letter state code (CA, TX, NY, etc.)
zip_code	string	Five-digit ZIP code
county	string	County name
fips_code	string	Five-digit Federal FIPS county code
latitude	number	Latitude coordinate (WGS 84)
longitude	number	Longitude coordinate (WGS 84)
neighborhoods	array	Associated neighborhood or subdivision names
description	string	Full marketing description from the listing
tags	array	Amenity and feature tags
pets_dogs	boolean	True if dogs are permitted
pets_cats	boolean	True if cats are permitted
agent_name	string	Listing agent full name
agent_email	string	Listing agent email address
agent_phone	string	Listing agent phone number
agent_office	string	Real estate office name
agent_broker	string	Managing broker name
co_agent_name	string	Co-listing agent name
co_agent_phone	string	Co-listing agent phone
tax_record_id	string	Public tax record identifier
primary_photo	string	Cover photo URL
photos	array	All property photo URLs
open_houses	array	Scheduled open house events with dates and times
details	array	Detailed property attributes by category (appliances, heating, construction, etc.)

📤 Example Output

{
  "processor": "https://apify.com/cheapget/us-real-estate?fpr=aiagentapi",
  "processed_at": "2026-03-06T10:30:00+00:00",
  "property_url": "https://www.example.com/property/350-5th-Ave_New-York_NY_10118",
  "property_id": "M9234718495",
  "listing_id": "2961478523",
  "mls_id": "NYMLS",
  "mls_listing_id": "H6298471",
  "status": "for_sale",
  "mls_status": "Active",
  "is_new_construction": false,
  "is_contingent": false,
  "is_pending": false,
  "date_listed": "2026-01-15",
  "date_pending": null,
  "date_sold": null,
  "date_updated": "2026-03-01",
  "date_status_changed": "2026-01-15T09:00:00Z",
  "list_price": 1250000,
  "list_price_min": null,
  "list_price_max": null,
  "sold_price": null,
  "price_per_sqft": 892,
  "hoa_fee": 1850,
  "estimated_value": 1180000,
  "estimated_high": 1290000,
  "estimated_low": 1070000,
  "property_type": "condos",
  "beds": 2,
  "baths_full": 2,
  "baths_half": 1,
  "sqft": 1401,
  "lot_sqft": null,
  "year_built": 2018,
  "garage_spaces": 1,
  "stories": 1,
  "address": "350 5th Ave",
  "unit": "Apt 42F",
  "city": "New York",
  "state": "NY",
  "zip_code": "10118",
  "county": "New York",
  "fips_code": "36061",
  "latitude": 40.7484,
  "longitude": -73.9857,
  "neighborhoods": ["Midtown Manhattan", "Murray Hill"],
  "description": "Stunning 2BR/2.5BA condo with panoramic city views from the 42nd floor. Floor-to-ceiling windows, chef's kitchen with Sub-Zero appliances, marble bathrooms, and in-unit washer/dryer. Full-service building with 24/7 doorman, gym, rooftop terrace, and residents' lounge.",
  "tags": ["doorman", "gym", "rooftop", "washer_dryer", "parking"],
  "pets_dogs": true,
  "pets_cats": true,
  "agent_name": "Sarah Chen",
  "agent_email": "sarah.chen@luxurynyc.com",
  "agent_phone": "(212) 555-0198",
  "agent_office": "Luxury NYC Realty",
  "agent_broker": "Manhattan Premier Group",
  "co_agent_name": "Michael Torres",
  "co_agent_phone": "(212) 555-0234",
  "tax_record_id": "1-00987-0042F",
  "primary_photo": "https://photos.example.com/property/M9234718495/cover.jpg",
  "photos": [
    "https://photos.example.com/property/M9234718495/photo1.jpg",
    "https://photos.example.com/property/M9234718495/photo2.jpg",
    "https://photos.example.com/property/M9234718495/photo3.jpg"
  ],
  "open_houses": [
    {
      "start_date": "2026-03-08T13:00:00",
      "end_date": "2026-03-08T15:00:00",
      "description": "Open House - Saturday 1-3 PM"
    }
  ],
  "details": [
    {
      "category": "Bedrooms",
      "text": ["Primary Bedroom: 15x12", "Bedroom 2: 12x10"]
    },
    {
      "category": "Heating and Cooling",
      "text": ["Central Air", "Forced Air Heating"]
    }
  ]
}

🔌 Integrations

Seamlessly connect this actor to your existing pipelines via the Apify API.

Ⓜ️ Make.com Integration

Get Started with Make.com (1000 Free Credits) 🎁

┌────────────────────────────────────────────┐
│  Step 1: Configure Actor Module            │
│  ├─ Add Module: "Run an Actor"             │
│  ├─ Enable Map: Toggle ON                  │
│  ├─ Actor ID: cheapget/us-real-estate     │
│  ├─ Refresh: Click Refresh button          │
│  └─ Input JSON: Add search parameters      │
└────────────────────────────────────────────┘
         ↓
┌────────────────────────────────────────────┐
│  Step 2: Set Execution Mode                │
│  └─ Run synchronously: YES                 │
└────────────────────────────────────────────┘
         ↓
┌────────────────────────────────────────────┐
│  Step 3: Retrieve Results                  │
│  ├─ Add Module: "Get Dataset Items"        │
│  └─ Dataset ID: defaultDatasetId           │
└────────────────────────────────────────────┘

🎱 N8N.io Integration

Open Source Workflow Automation ⚡

┌────────────────────────────────────────────┐
│  Step 1: Add Apify Node                    │
│  ├─ Search: "Run an Actor and get dataset" │
│  └─ Category: Apify                        │
└────────────────────────────────────────────┘
         ↓
┌────────────────────────────────────────────┐
│  Step 2: Configure Actor                   │
│  ├─ Selection Mode: By ID                  │
│  ├─ Actor ID: cheapget/us-real-estate     │
│  └─ Paste from Actor ID section above      │
└────────────────────────────────────────────┘
         ↓
┌────────────────────────────────────────────┐
│  Step 3: Set Input Parameters              │
│  └─ Modify Input JSON with search criteria │
└────────────────────────────────────────────┘

📚 API Documentation

• MCP API - Model Context Protocol integration
• Python API - Complete Python client documentation with examples
• JavaScript API - Node.js and browser integration guide

🏗️ Metadata for Developers (JSON-LD)

{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "US Real Estate - Property Listing Scraper",
  "alternateName": [
    "Real Estate API",
    "Property Listing Scraper",
    "Home Listing Extractor",
    "MLS Listing Scraper"
  ],
  "applicationCategory": "DeveloperApplication",
  "applicationSubCategory": "Real Estate Data Extraction",
  "operatingSystem": "Cloud",
  "offers": {
    "@type": "Offer",
    "price": "0.00",
    "priceCurrency": "USD",
    "priceValidUntil": "2099-12-31",
    "availability": "https://schema.org/InStock"
  },
  "description": "Extract comprehensive property listings across the entire US. Search by ZIP code, city, state, or address. Get pricing, specs, agent contacts, valuations, MLS data, photos, and open houses for sales, rentals, sold, and pending properties.",
  "featureList": [
    "Flexible US location search (ZIP, city, state, address, neighborhood, county)",
    "7 listing types: sale, rent, sold, pending, off-market, new community, ready-to-build",
    "50+ data fields per property",
    "Automated valuation estimates (AVM) with high/low range",
    "Agent and broker contact details (email, phone, office)",
    "MLS board ID and listing ID for cross-referencing",
    "Property photos, primary photo, and open house schedules",
    "Geographic coordinates for mapping and geospatial analysis",
    "Pet policy, tax records, and FIPS codes",
    "Export to JSON, CSV, Excel formats"
  ],
  "keywords": "real estate api, property scraper, property listing scraper, mls scraper, property listing api, home scraper, real estate data extraction, property valuation api, house listing scraper, real estate market data, property search api, home price data, real estate lead generation, agent contact scraper, property data api, housing data api, home listing scraper, housing market data, property listing extractor, real estate analytics, home value estimator, mls data api, property photo scraper, open house data, hoa fee data, real estate automation",
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.9",
    "ratingCount": "500",
    "bestRating": "5"
  },
  "author": {
    "@type": "Organization",
    "name": "cheapget",
    "url": "https://apify.com/cheapget?fpr=aiagentapi"
  },
  "softwareVersion": "0.1",
  "datePublished": "2026-03-06",
  "dateModified": "2026-03-08"
}

🚀 Performance Tips

Optimize your extraction runs for speed, cost, and data quality with these best practices:

💰 Cost Optimization

• Test First: Start with max_results: 100 (minimum) before scaling up. Each property costs $0.00189.
• Target Specific Areas: Use city + state (Austin, TX) instead of broad state-level searches to reduce irrelevant results.

⚡ Speed Optimization

• Smaller Regions: ZIP codes and neighborhoods return faster than full state or county searches.
• Recent Listings: Use listed_since: "30 days" instead of "1 year" for faster results with fewer properties.

🛡️ Data Quality Tips

• Location Format: Use City, ST format (e.g., Austin, TX) for best results. Abbreviated state codes alone (e.g., TX) are not supported — use full state names (Texas).
• Valuation Data: Not all properties have AVM estimates. Filter by estimated_value to get properties with valuation data.
• Agent Contacts: Agent email and phone availability varies by listing. MLS rules may restrict certain contact details.
• Sold Data: Use listing_type: "sold" with listed_since to analyze recent comparable sales (comps).

📊 Best Practices

• Deduplication: The Actor automatically deduplicates results by property ID.
• Per-Type Runs: To collect multiple listing types, run the Actor once per type (e.g., one run for for_sale, another for for_rent). max_results applies to each run independently.
• Scheduling: Set up daily or weekly runs for market monitoring. Property data changes frequently as new listings appear and prices adjust.

❓ FAQ

What locations can I search?

You can search any US location: ZIP codes (10001), cities (Austin), city + state (Austin, TX or Austin, Texas), full addresses (350 5th Ave, New York, NY 10118), neighborhoods (South Beach), counties (Cook County), or full state names (Texas). Note: abbreviated state codes alone (e.g., TX) are not supported.

What listing types are available?

Seven listing types are supported: for_sale, for_rent, sold, pending, off_market, new_community, and ready_to_build. Each run searches one listing type. Run the Actor separately to collect different types.

How many properties can I extract?

Up to 10,000 properties per run. Each run searches one listing type. To collect multiple types, run the Actor separately for each (e.g., one run for for_sale, one for sold).

What are the automated valuation estimates?

The estimated_value, estimated_high, and estimated_low fields come from automated valuation models (AVM). These are algorithmic property value estimates — not appraisals. They provide a useful reference point but may not reflect exact market value.

Why are some agent emails or phones missing?

Agent contact information depends on MLS rules and listing agent preferences. Some boards restrict email or phone display. The Actor extracts all available contact data from each listing.

How do I find comparable sales (comps)?

Set listing_type to "sold" and listed_since to a recent period like "6 months". Filter the results by location, property type, and size to find relevant comparables for valuation analysis.

How long does a typical run take?

Runtime depends on the location scope and max_results. A typical run with 500 properties completes in 1–3 minutes. Broad state-level searches or 10,000 results may take 5–10 minutes.

What output formats are available?

The Actor outputs data in JSON format by default. You can export results to CSV or Excel formats using Apify's dataset export features in the Output tab.

Can I filter by price range or number of bedrooms?

The Actor supports filtering by property type (single family, condos, etc.) and listing date. For price or bedroom filters, extract the full dataset and filter the results using the list_price, beds, and other fields in your pipeline.

🏷️ US Real Estate

🔥 Search Terms: real estate api, property scraper, property listing scraper, mls scraper, property listing api, home scraper, real estate data extraction, property valuation api, house listing scraper, real estate market data, property search api, home price data, real estate lead generation, agent contact scraper, property data api, housing data api, home listing scraper, housing market data, property listing extractor, real estate analytics, home value estimator, mls data api, property photo scraper, open house data, hoa fee data, real estate automation, property comps api, real estate investment data, rental property scraper, foreclosure data

💼 Use Case: real-estate-analytics property-valuation market-research lead-generation comp-analysis investment-research rental-market-analysis agent-prospecting property-monitoring housing-market-trends real-estate-investment appraisal-data mls-data-extraction property-portfolio-tracking neighborhood-analysis

⚖️ Legal & Compliance

This actor extracts publicly available data only. It does not bypass authentication, access private content, or violate platform terms of service. You are responsible for:

• Data Rights: Ensuring you have permission to collect and use the extracted data
• Privacy Compliance: Adhering to GDPR, CCPA, and other applicable privacy laws when processing data
• Platform Terms: Respecting the platform's terms of service and usage policies
• Ethical Use: Using extracted data responsibly and in compliance with applicable laws

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Last Updated: March 8, 2026