Realtor Property Scraper
Pricing
from $2.20 / 1,000 results
Realtor Property Scraper
Realtor.com search across all 50 US states with 8 listing statuses (for_sale, for_rent, sold, pending, off_market, new_community, ready_to_build, other) and 11 property types. Each result returns address, beds/baths, sqft, list/sold price, days-on-market, agent + broker contact, and MLS ID.
Pricing
from $2.20 / 1,000 results
Rating
5.0
(2)
Developer
AgentX
Maintained by CommunityActor stats
2
Bookmarked
23
Total users
8
Monthly active users
1.5 hours
Issues response
5 days ago
Last modified
Categories
Share
Realtor Property Scraper - US Real Estate Listings Intelligence API
Realtor Property Scraper is a US real-estate listings intelligence API that extracts structured Realtor.com property records, MLS data, AVM valuations, and agent-contact signals across all 50 US states and 8 listing types in a single location/MLS-driven run. Realtor Property Scraper returns structured records per property, including MLS ID and status, AVM valuation, list price, price-cut history, days-on-market (DOM), bedrooms, bathrooms, square footage, lot size, year built, HOA fees, tax history, advertisers array (agent name/email/office/type), broker ID, nearby schools array, photo URL array, listing URL, and full address. Coverage spans for-sale, for-rent, sold, pending, off-market, new-community, ready-to-build, and other listings across all 50 US states. Built for US real-estate market research, MLS-grade investment analysis, agent-lead generation, AVM benchmarking, REI deal sourcing, PropTech CRM enrichment, and broker-intelligence pipelines. Up to 50,000 property records per run, with pay-per-result pricing at $0.0024 per record and no monthly minimum.
Why Choose This API
Structured Realtor.com MLS Intelligence for Real Estate Pipelines
๐ 7-Listing-Type Coverage
Switch between for_sale, for_rent, sold, pending, off_market, new_community, and ready_to_build via the listing_type parameter โ covering every US real estate market segment from active resale to new construction for comprehensive property intelligence.
๐ฐ AVM Valuation Intelligence
The current_estimates and estimates fields deliver Automated Valuation Model (AVM) data per property โ including estimate value, high/low range, and estimate date for investment underwriting, portfolio valuation, and market benchmarking workflows.
๐
Price-Cut & Days-on-Market Signals
The last_status_change_date, list_date, and pending_date fields enable days-on-market calculation and price event detection โ building market velocity signals, listing freshness scores, and price reduction timeseries for real estate analytics.
๐ค Agent & Broker Contact Intelligence
The advertisers array captures agent name, email, type, and office data per listing โ enabling agent lead enrichment, broker contact extraction, and real estate CRM pipeline population for market participant intelligence.
๐๏ธ MLS Status & Source Intelligence
The mls_status and source fields capture the exact MLS status string and originating board ID โ enabling cross-MLS deduplication, listing source attribution, and MLS data aggregation across Realtor.com's national coverage.
๐ซ Nearby Schools & HOA Intelligence
The nearby_schools and hoa fields deliver neighborhood context and ownership cost data per property โ supporting school-district-level market segmentation, buyer persona targeting, and full cost-of-ownership analysis pipelines.
Quick Start Guide
How to Extract Realtor.com Property Data in 3 Steps
Step 1: Define Location and Listing Type
Enter any US location (ZIP, city, address, county, neighborhood, or full state name) and select the listing type.
Step 2: Configure and Run the Actor
Set location, listing type, optional date filter, optional property type, and max results. Click Start.
Step 3: Download Your Data
Export results as JSON or CSV, or access programmatically via the Apify dataset API.
Input Parameters
Configuration Fields
| Parameter | Type | Required | Description | Example Values |
|---|---|---|---|---|
location | string | โ | US location: ZIP, city, city+state, address, neighborhood, county, or state | "New York, NY", "10001", "Austin, TX", "Texas" |
listing_type | select | โ | Listing market segment | "for_sale", "for_rent", "sold", "pending", "off_market", "new_community", "ready_to_build" |
listed_since | date | โ | Filter by listing recency | "1 year", "6 months", absolute date |
property_type | select | โ | Property style filter (leave empty for all) | "single_family", "condos", "multi_family", "land", "mobile" |
max_results | integer | โ | Maximum property records to extract | 50, 200, 1000 |
Example Input Configuration
{"location": "Austin, TX","listing_type": "for_sale","listed_since": "6 months","property_type": ["single_family", "condos"],"max_results": 200}
Output Data Schema
Complete Property Record Structure
Each extracted Realtor.com property record contains the following fields:
Core Property Fields
| Field | Type | Description |
|---|---|---|
processor | string | Apify actor URL that processed this record |
processed_at | string | ISO 8601 timestamp (UTC) when scraped |
cover_image | string | Primary listing image URL |
listing_id | string | Unique listing identifier |
property_id | string | Unique property identifier |
href | string | Full listing URL on Realtor.com |
permalink | string | Listing URL slug |
list_price | number | Current listing price (USD) |
list_price_min | number | Minimum price for range-priced listings |
list_price_max | number | Maximum price for range-priced listings |
price_per_sqft | number | Price per square foot (USD) |
status | string | Listing status (for_sale, sold, etc.) |
mls_status | string | Exact MLS status string |
list_date | string | Date when first listed |
last_sold_date | string | Most recent sale date |
last_sold_price | number | Most recent sale price |
last_status_change_date | string | Date of last status change |
last_update_date | string | Date of last data update |
pending_date | string | Date entered pending status |
description | object | Property details (beds, baths, sqft, type, year built, text) |
location | object | Full address, city, state, ZIP, county, coordinates |
advertisers | array | Agent/broker name, email, type, office |
current_estimates | array | AVM valuation estimates |
estimates | object | Grouped AVM estimate data |
details | array | Categorized listing facts (appliances, school info) |
flags | object | Listing flags (pending, contingent, new construction) |
hoa | object | HOA fee information |
nearby_schools | object | Nearby school district data |
photos | array | Photo gallery with image URLs |
primary_photo | object | Primary listing photo |
open_houses | array | Scheduled open house entries |
tax_record | object | Tax record identifiers |
tax_history | array | Historical tax and assessment data |
parking | object | Parking details and availability |
pet_policy | object | Pet allowance policy |
tags | array | Feature and amenity tags |
popularity | object | Clicks, views, saves, dwell time |
monthly_fees | array | Recurring monthly fees |
one_time_fees | array | One-time listing/rental fees |
terms | array | Lease or listing terms |
units | array | Unit-level data for multi-unit listings |
source | object | MLS board ID and listing reference |
Example JSON Output
{"processor": "https://apify.com/agentx/realtor-property-scraper?fpr=aiagentapi","processed_at": "2026-05-01T10:30:00.000Z","listing_id": "2983158636","property_id": "1015318600","list_price": 99900,"price_per_sqft": 131,"status": "for_sale","mls_status": "Active","description": {"type": "condos","sqft": 761,"beds": 1,"baths_full": 1,"year_built": 1911},"location": {"address": {"line": "2083 NW Johnson St Apt 5","city": "Portland","state_code": "OR","postal_code": "97209"}},"advertisers": [{"email": "agent@example.com","type": "seller","name": "Daniel M"}]}
Export Formats
- JSON - Complete structured data with all metadata
- CSV - Spreadsheet-compatible for BI and analytics tools
- API Access - Programmatic access via Apify Client SDK
- Cloud Storage - Automatic upload to Apify Dataset
Integration Examples
Actor ID for Platform Integration
eou9sUeDcGLZomwXL
โ๏ธ Make.com Setup:
- Login to Make.com (Get 1000 Free Credits)
- Add module "Run an Actor"
- Turn 'Map' on - right side of the 'Actor*'
- Paste Actor ID - from above
- Click the 'โณ Refresh' - left side of Map
- Input JSON* - Modify the parameters as needed
- Set "Run synchronously" to YES
- Add module "Get Dataset Items" - receive the result
- In Dataset ID* select defaultDatasetId
๐ฑ N8N.io Setup:
- Add 'Run an Actor and get dataset' - from the apify node
- Actor โ By ID โ Paste Actor ID - from above
- Input JSON - Modify the parameters as needed
Python Integration Example
from apify_client import ApifyClientclient = ApifyClient('YOUR_API_TOKEN')run_input = {"location": "Austin, TX","listing_type": "for_sale","max_results": 500}run = client.actor("eou9sUeDcGLZomwXL").call(run_input=run_input)for item in client.dataset(run["defaultDatasetId"]).iterate_items():print(item)
JavaScript/Node.js Integration
import { ApifyClient } from "apify-client";const client = new ApifyClient({ token: "YOUR_API_TOKEN" });const input = {location: "Miami, FL",listing_type: "for_rent",max_results: 200,};const run = await client.actor("eou9sUeDcGLZomwXL").call(input);const { items } = await client.dataset(run.defaultDatasetId).listItems();items.forEach((item) => console.log(item));
JSON-LD Metadata
{"@context": "https://schema.org","@graph": [{"@type": "SoftwareApplication","@id": "https://apify.com/agentx/realtor-property-scraper?fpr=aiagentapi#software","name": "Realtor Property Scraper","description": "Realtor Property Scraper is a US real-estate listings intelligence API extracting structured Realtor.com MLS data, AVM valuations, price-cut history, days-on-market, agent contacts, HOA fees, nearby schools, and tax records across all 50 US states and 8 listing types.","applicationCategory": "BusinessApplication","applicationSubCategory": "Web Scraping API","operatingSystem": "Web, Cloud","url": "https://apify.com/agentx/realtor-property-scraper?fpr=aiagentapi","softwareVersion": "1.0.0","datePublished": "2024-08-01","dateModified": "2026-05-17","featureList": ["MLS ID, status, board ID, and AVM valuation","Price-cut history and days-on-market (DOM)","Bedrooms, bathrooms, sqft, lot size, year built","HOA fees, tax history, and nearby schools","Advertisers array with agent email and office","All 50 US states across 8 listing types","Up to 50,000 property records per run","Native integrations with Make.com, n8n, LangChain, and CrewAI"],"offers": {"@type": "Offer","price": "0.0024","priceCurrency": "USD","availability": "https://schema.org/InStock"},"author": { "@id": "https://apify.com/agentx?fpr=aiagentapi#person" },"publisher": { "@id": "https://apify.com?fpr=aiagentapi#organization" }},{"@type": "Person","@id": "https://apify.com/agentx?fpr=aiagentapi#person","name": "AgentX","url": "https://apify.com/agentx?fpr=aiagentapi","sameAs": ["https://apify.com/agentx?fpr=aiagentapi","https://t.me/AiAgentApi","https://t.me/Apify_Actor"],"knowsAbout": ["web scraping","Realtor.com","US real estate","MLS data","PropTech"]},{"@type": "BreadcrumbList","itemListElement": [{"@type": "ListItem","position": 1,"name": "Apify","item": "https://apify.com?fpr=aiagentapi"},{"@type": "ListItem","position": 2,"name": "AgentX","item": "https://apify.com/agentx?fpr=aiagentapi"},{"@type": "ListItem","position": 3,"name": "Realtor Property Scraper","item": "https://apify.com/agentx/realtor-property-scraper?fpr=aiagentapi"}]}]}
Pricing & Cost Calculator
Pay-Per-Result Pricing
| Event | Rate |
|---|---|
| Actor Start | $0.01 per GB memory |
| Result (per property) | $0.0024 (BRONZE tier) |
Cost Calculator Examples
| Results | Estimated Cost |
|---|---|
| 100 properties | ~$0.24 |
| 500 properties | ~$1.20 |
| 1,000 properties | ~$2.40 |
| 5,000 properties | ~$12.00 |
| 10,000 properties | ~$24.00 |
Actual cost varies by Apify plan tier. Higher tiers (SILVER โ DIAMOND) unlock lower per-result rates down to $0.0022 per property.
Use Cases & Applications
Real Estate Market Research & Investment Analysis
Market Price Intelligence
Extract list_price, price_per_sqft, last_sold_price, and current_estimates across ZIP codes or cities โ building US residential market price benchmarks, appreciation rate analysis, and investment opportunity scoring for real estate data pipelines.
Days-on-Market Velocity Tracking
Compute days-on-market from list_date and last_status_change_date โ building market velocity signals, listing freshness scores, and supply/demand indicators for real estate market intelligence.
AVM Portfolio Valuation
Extract current_estimates with estimate high/low ranges โ building automated portfolio valuation pipelines, investment underwriting workflows, and property assessment tools for real estate technology platforms.
Lead Generation & CRM Enrichment
Agent & Broker Lead Extraction
The advertisers array delivers agent name, email, and office data per listing โ enabling real estate agent lead generation, broker database building, and CRM pipeline enrichment for proptech platforms.
Sold Listing Lead Intelligence
Target listing_type: "sold" to extract recently transacted properties and their agents โ identifying active deal-making agents for market participation analysis and recent transaction lead sourcing.
Multi-State Investment Opportunity Scanning Run parallel location queries across states โ building multi-state property opportunity datasets for institutional investors, portfolio managers, and real estate fund research operations.
FAQ
What US locations are supported?
All 50 US states. Accepted location formats include ZIP code, city, city+state (e.g., "Austin, TX"), full address, neighborhood, county, and full state name (e.g., "Texas").
What listing types are available?
for_sale, for_rent, sold, pending, off_market, new_community, other, and ready_to_build.
Does the actor extract agent contact details?
Yes โ the advertisers array includes agent name, email, type (seller/buyer/listing), and office information per listing.
What property types can I filter by?
Single family, multi-family, apartment, condos, condo/townhome, townhomes, duplex/triplex, farm, land, and mobile.
How does this compare to Zillow For Sale Scraper?
Both provide US property intelligence. Use Zillow For Sale Scraper for Zillow-specific records, and this actor for Realtor.com MLS data โ combine both for comprehensive US residential market coverage.
SEO Keywords & Search Terms
Primary Keywords
Realtor.com property scraper API, MLS data extraction API, US real estate data API, Realtor listing intelligence, property data pipeline, real estate lead generation API, Realtor.com listing scraper, MLS property API, US housing market data, real estate intelligence API
Long-Tail Keywords
how to extract Realtor.com property data programmatically, Realtor.com MLS data API, US real estate price history API, realtor agent contact extraction, AVM valuation data API, property days-on-market API, Realtor.com sold listings scraper, US property price per sqft API, real estate lead enrichment pipeline, all 50 states real estate data
Industry Terms
MLS data extraction API, AVM property valuation intelligence, real estate market velocity API, property listing status API, days-on-market data, agent contact intelligence, broker ID extraction, real estate CRM enrichment, HOA fee data API, US residential market data
Use Case Keywords
property investment data API, real estate lead pipeline, Realtor.com price monitor, sold listing intelligence, agent email extraction, multi-state property research, rental listing data API, real estate portfolio valuation, housing market analysis API, school district property data
Trust & Certifications
- โ Production-Grade Infrastructure โ runs on the Apify cloud platform with managed proxy rotation and automatic retries
- โ GDPR & CCPA-Region Aligned โ extracts only publicly available Realtor.com listings; no personal contact data retained beyond the run session
- โ Pay-Per-Result Billing โ transparent $0.0024 per property with no monthly minimum or seat fees
- โ Continuously Maintained โ schema and selector updates released as Realtor.com evolves
Legal & Compliance
Data Rights & Usage
All data extracted by this actor originates from publicly available Realtor.com listing data. Users are responsible for ensuring their use of extracted data complies with applicable laws, NAR/MLS data use policies, and Realtor.com terms of service.
Privacy Compliance
- GDPR: Compliant with EU GDPR for data processing workflows.
- CCPA: Compliant with California Consumer Privacy Act requirements.
Platform Terms of Service
Users must review and comply with Realtor.com and MLS data use terms when using extracted data.
Enterprise Support
For enterprise licensing, custom integrations, or compliance inquiries:
- Telegram: @AiAgentApi
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- ๐ฅ Community: @Apify_Actor
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Last Updated: May 17, 2026