Property Listing Aggregation API - Real Estate Data Collection

Real Estate Data Is Fragmented

Property listings are scattered across dozens of platforms - MLS feeds, real estate portals, broker websites, and classified sites. Building a comprehensive view requires aggregating from all sources.

Each platform has different data formats, access restrictions, and update frequencies. Manual collection is impossible at scale.

WebScraping.AI Solution

Multi-Platform Coverage: Collect listings from any real estate website
Complete Data: Extract price, specs, photos, descriptions, and agent info
JavaScript Rendering: Handle modern real estate sites with dynamic loading
Structured Output: Get uniform JSON regardless of source platform

Property Data Extraction

Capture every detail from property listings

Pricing Data

List price, price history, price per sqft, and estimated values.

Property Details

Beds, baths, sqft, lot size, year built, and amenities.

Photos & Tours

All listing photos, virtual tour links, and floor plans.

Agent Info

Listing agent, brokerage, and contact information.

How It Works

Aggregate property listings in three steps

1

Define Sources

Identify the real estate platforms and listing pages you want to collect from.

2

Extract Data

Our AI extracts all property details, photos, and agent info from each listing.

3

Build Database

Store structured listing data in your property database or application.

Code Examples

Extract property listing data from any real estate site

curl -G "https://api.webscraping.ai/ai/fields" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://example-realestate.com/listing/123-main-st" \
  --data-urlencode "fields[address]=Full property address" \
  --data-urlencode "fields[price]=Listing price as a number" \
  --data-urlencode "fields[bedrooms]=Number of bedrooms" \
  --data-urlencode "fields[bathrooms]=Number of bathrooms" \
  --data-urlencode "fields[sqft]=Square footage" \
  --data-urlencode "fields[lot_size]=Lot size" \
  --data-urlencode "fields[year_built]=Year the property was built" \
  --data-urlencode "fields[property_type]=Type of property (house, condo, etc)" \
  --data-urlencode "fields[description]=Property description" \
  --data-urlencode "fields[photos]=Array of all photo URLs" \
  --data-urlencode "fields[agent_name]=Listing agent name" \
  --data-urlencode "fields[agent_phone]=Agent phone number" \
  --data-urlencode "fields[days_on_market]=Days the listing has been active"
# Response:
# {
#   "address": "123 Main Street, Austin, TX 78701",
#   "price": 549000,
#   "bedrooms": 3,
#   "bathrooms": 2,
#   "sqft": 1850,
#   "lot_size": "0.25 acres",
#   "year_built": 2018,
#   "property_type": "Single Family Home",
#   "description": "Beautiful modern home...",
#   "photos": ["https://...", "https://...", ...],
#   "agent_name": "Jane Smith",
#   "agent_phone": "(512) 555-0123",
#   "days_on_market": 14
# }

# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client

client = Client(api_key="YOUR_API_KEY")
result = client.fields(
    "https://example-realestate.com/listing/123-main-st",
    fields={
        "address": "Full property address",
        "price": "Listing price as a number",
        "bedrooms": "Number of bedrooms",
        "bathrooms": "Number of bathrooms",
        "sqft": "Square footage",
        "lot_size": "Lot size",
        "year_built": "Year the property was built",
        "property_type": "Type of property (house, condo, etc)",
        "description": "Property description",
        "photos": "Array of all photo URLs",
        "agent_name": "Listing agent name",
        "agent_phone": "Agent phone number",
        "days_on_market": "Days the listing has been active",
    },
)
print(result)
# Response:
# {
#   "address": "123 Main Street, Austin, TX 78701",
#   "price": 549000,
#   "bedrooms": 3,
#   "bathrooms": 2,
#   "sqft": 1850,
#   "lot_size": "0.25 acres",
#   "year_built": 2018,
#   "property_type": "Single Family Home",
#   "description": "Beautiful modern home...",
#   "photos": ["https://...", "https://...", ...],
#   "agent_name": "Jane Smith",
#   "agent_phone": "(512) 555-0123",
#   "days_on_market": 14
# }

// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';

const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const result = await client.fields({
  url: 'https://example-realestate.com/listing/123-main-st',
  fields: {
    address: 'Full property address',
    price: 'Listing price as a number',
    bedrooms: 'Number of bedrooms',
    bathrooms: 'Number of bathrooms',
    sqft: 'Square footage',
    lot_size: 'Lot size',
    year_built: 'Year the property was built',
    property_type: 'Type of property (house, condo, etc)',
    description: 'Property description',
    photos: 'Array of all photo URLs',
    agent_name: 'Listing agent name',
    agent_phone: 'Agent phone number',
    days_on_market: 'Days the listing has been active',
  },
});
console.log(result);
// Response:
// {
//   "address": "123 Main Street, Austin, TX 78701",
//   "price": 549000,
//   "bedrooms": 3,
//   "bathrooms": 2,
//   "sqft": 1850,
//   "lot_size": "0.25 acres",
//   "year_built": 2018,
//   "property_type": "Single Family Home",
//   "description": "Beautiful modern home...",
//   "photos": ["https://...", "https://...", ...],
//   "agent_name": "Jane Smith",
//   "agent_phone": "(512) 555-0123",
//   "days_on_market": 14
// }

<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';

use WebScrapingAI\Client;

$client = new Client('YOUR_API_KEY');
$result = $client->fields('https://example-realestate.com/listing/123-main-st', [
    'address'        => 'Full property address',
    'price'          => 'Listing price as a number',
    'bedrooms'       => 'Number of bedrooms',
    'bathrooms'      => 'Number of bathrooms',
    'sqft'           => 'Square footage',
    'lot_size'       => 'Lot size',
    'year_built'     => 'Year the property was built',
    'property_type'  => 'Type of property (house, condo, etc)',
    'description'    => 'Property description',
    'photos'         => 'Array of all photo URLs',
    'agent_name'     => 'Listing agent name',
    'agent_phone'    => 'Agent phone number',
    'days_on_market' => 'Days the listing has been active',
]);
print_r($result);
// Response:
// {
//   "address": "123 Main Street, Austin, TX 78701",
//   "price": 549000,
//   "bedrooms": 3,
//   "bathrooms": 2,
//   "sqft": 1850,
//   "lot_size": "0.25 acres",
//   "year_built": 2018,
//   "property_type": "Single Family Home",
//   "description": "Beautiful modern home...",
//   "photos": ["https://...", "https://...", ...],
//   "agent_name": "Jane Smith",
//   "agent_phone": "(512) 555-0123",
//   "days_on_market": 14
// }

# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'

client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
result = client.fields(
  'https://example-realestate.com/listing/123-main-st',
  fields: {
    address:         'Full property address',
    price:           'Listing price as a number',
    bedrooms:        'Number of bedrooms',
    bathrooms:       'Number of bathrooms',
    sqft:            'Square footage',
    lot_size:        'Lot size',
    year_built:      'Year the property was built',
    property_type:   'Type of property (house, condo, etc)',
    description:     'Property description',
    photos:          'Array of all photo URLs',
    agent_name:      'Listing agent name',
    agent_phone:     'Agent phone number',
    days_on_market:  'Days the listing has been active',
  }
)
puts result.inspect
# Response:
# {
#   "address": "123 Main Street, Austin, TX 78701",
#   "price": 549000,
#   "bedrooms": 3,
#   "bathrooms": 2,
#   "sqft": 1850,
#   "lot_size": "0.25 acres",
#   "year_built": 2018,
#   "property_type": "Single Family Home",
#   "description": "Beautiful modern home...",
#   "photos": ["https://...", "https://...", ...],
#   "agent_name": "Jane Smith",
#   "agent_phone": "(512) 555-0123",
#   "days_on_market": 14
# }

// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main

import (
    "context"
    "fmt"

    webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)

func main() {
    client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
    result, _ := client.Fields(context.Background(), &webscrapingai.FieldsOptions{
        URL: "https://example-realestate.com/listing/123-main-st",
        Fields: map[string]string{
            "address": "Full property address",
            "price": "Listing price as a number",
            "bedrooms": "Number of bedrooms",
            "bathrooms": "Number of bathrooms",
            "sqft": "Square footage",
            "lot_size": "Lot size",
            "year_built": "Year the property was built",
            "property_type": "Type of property (house, condo, etc)",
            "description": "Property description",
            "photos": "Array of all photo URLs",
            "agent_name": "Listing agent name",
            "agent_phone": "Agent phone number",
            "days_on_market": "Days the listing has been active",
        },
    })
    fmt.Println(result.Result)
}
// Response:
// {
//   "address": "123 Main Street, Austin, TX 78701",
//   "price": 549000,
//   "bedrooms": 3,
//   "bathrooms": 2,
//   "sqft": 1850,
//   "lot_size": "0.25 acres",
//   "year_built": 2018,
//   "property_type": "Single Family Home",
//   "description": "Beautiful modern home...",
//   "photos": ["https://...", "https://...", ...],
//   "agent_name": "Jane Smith",
//   "agent_phone": "(512) 555-0123",
//   "days_on_market": 14
// }

// Maven: ai.webscraping:webscraping-ai:4.0.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.FieldsOptions;
import ai.webscraping.result.FieldsResult;

Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
FieldsResult result = client.fields(FieldsOptions.builder()
    .url("https://example-realestate.com/listing/123-main-st")
    .addField("address", "Full property address")
    .addField("price", "Listing price as a number")
    .addField("bedrooms", "Number of bedrooms")
    .addField("bathrooms", "Number of bathrooms")
    .addField("sqft", "Square footage")
    .addField("lot_size", "Lot size")
    .addField("year_built", "Year the property was built")
    .addField("property_type", "Type of property (house, condo, etc)")
    .addField("description", "Property description")
    .addField("photos", "Array of all photo URLs")
    .addField("agent_name", "Listing agent name")
    .addField("agent_phone", "Agent phone number")
    .addField("days_on_market", "Days the listing has been active")
    .build());
System.out.println(result.getResult());
// Response:
// {
//   "address": "123 Main Street, Austin, TX 78701",
//   "price": 549000,
//   "bedrooms": 3,
//   "bathrooms": 2,
//   "sqft": 1850,
//   "lot_size": "0.25 acres",
//   "year_built": 2018,
//   "property_type": "Single Family Home",
//   "description": "Beautiful modern home...",
//   "photos": ["https://...", "https://...", ...],
//   "agent_name": "Jane Smith",
//   "agent_phone": "(512) 555-0123",
//   "days_on_market": 14
// }

// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;

var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var result = await client.FieldsAsync(new FieldsRequest {
    Url = "https://example-realestate.com/listing/123-main-st",
    Fields = new Dictionary<string, string> {
        ["address"] = "Full property address",
        ["price"] = "Listing price as a number",
        ["bedrooms"] = "Number of bedrooms",
        ["bathrooms"] = "Number of bathrooms",
        ["sqft"] = "Square footage",
        ["lot_size"] = "Lot size",
        ["year_built"] = "Year the property was built",
        ["property_type"] = "Type of property (house, condo, etc)",
        ["description"] = "Property description",
        ["photos"] = "Array of all photo URLs",
        ["agent_name"] = "Listing agent name",
        ["agent_phone"] = "Agent phone number",
        ["days_on_market"] = "Days the listing has been active",
    },
});
Console.WriteLine(result.Result);
// Response:
// {
//   "address": "123 Main Street, Austin, TX 78701",
//   "price": 549000,
//   "bedrooms": 3,
//   "bathrooms": 2,
//   "sqft": 1850,
//   "lot_size": "0.25 acres",
//   "year_built": 2018,
//   "property_type": "Single Family Home",
//   "description": "Beautiful modern home...",
//   "photos": ["https://...", "https://...", ...],
//   "agent_name": "Jane Smith",
//   "agent_phone": "(512) 555-0123",
//   "days_on_market": 14
// }

Benefits for Real Estate

Comprehensive Coverage: Aggregate listings from all major platforms in one database.

Always Current: Schedule regular scrapes to keep listings fresh.

Rich Media: Collect all photos and virtual tour links.

Market Analysis: Build datasets for pricing analysis and market trends.

Lead Generation: Capture agent and seller contact information.

Use Cases

Property Search Portals

Build comprehensive listing sites with data from multiple sources

Investment Analysis

Analyze property values and market trends

PropTech Applications

Power real estate apps with comprehensive listing data

Market Research

Track inventory levels, pricing trends, and market dynamics

Related Use Cases

Start Aggregating Property Data

Get started with 1,000 free API credits. No credit card required.

Start Free Trial View API Documentation

Property Listing Aggregation