# Realtor Property Data Scraper (`propertyapi/realtor-property-data-scraper`) Actor

Realtor Property Scraper allows you to extract detailed listing data from Realtor.com at scale. Monitor markets, track pricing trends, and build comprehensive property databases without the manual hassle.

- **URL**: https://apify.com/propertyapi/realtor-property-data-scraper.md
- **Developed by:** [Property API](https://apify.com/propertyapi) (community)
- **Categories:** Real estate, Developer tools, Lead generation
- **Stats:** 45 total users, 1 monthly users, 100.0% runs succeeded, 3 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $2.99 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Realtor Property Data Scraper

**The Ultimate Tool for Bulk Real Estate Data**

**Realtor Property Scraper** allows you to extract detailed listing data from Realtor.com at scale. Monitor markets, track pricing trends, and build comprehensive property databases without the manual hassle.

Whether you are an investor looking for the next deal or an analyst tracking inventory, this actor delivers structured, real-time data across any US market.

***

### 🏗️ Core Features

- **🌍 Multi-City Support**: Scrape listings from dozens of cities in a single run.
- **🏡 Granular Filtering**: Target specific property types (Single Family, Condos, Land, etc.).
- **📊 Smart Sorting**: Rank results by price, newness, lot size, or open house availability.
- **👥 Agent Details**: Automatically captures the listing agent's name, phone, and email with every property.
- **⚡ High Performance**: optimized for speed and reliability, handling large pagination depths easily.

***

### ⚙️ Configuration

Control exactly what data you get with flexible input parameters.

#### Input Parameters

| Parameter | Type | Required | Description |
| :--- | :--- | :--- | :--- |
| `cities` | Array | Yes | List of target cities (e.g., `["Austin", "Dallas"]`). |
| `status` | String | No | Filter by `for_sale` (default), `sold`, or `all`. |
| `property_type` | String | No | Filter by type (e.g., `single_family`, `condo`, `ANY`). |
| `sort_option` | String | No | Sort order (e.g., `newest`, `lowest price`). |
| `page_count` | Integer | No | Number of pages to scrape per city (default: 1). |

#### Example Input

**Investment Search:**

```json
{
  "cities": ["Atlanta", "Charlotte"],
  "page_count": 5,
  "property_type": "multi_family",
  "sort_option": "newest",
  "status": "for_sale"
}
```

**Sold Comps Analysis:**

```json
{
  "cities": ["Seattle"],
  "page_count": 10,
  "property_type": "single_family",
  "status": "sold",
  "sort_option": "newest"
}
```

***

### 📦 Output Data

Data is delivered in a clean, flattened JSON format for easy analysis.

```json
[
  {
    "city": "Atlanta",
    "data": {
      "results": [
        {
          "property_id": "92817452",
          "address": "123 Peachtree St, Atlanta, GA 30303",
          "list_price": 450000,
          "status": "for_sale",
          "beds": 3,
          "baths": "2.5",
          "sqft": 2100,
          "type": "single_family",
          "agent_name": "Sarah Smith",
          "agent_phone": "404-555-0123",
          "agent_email": "sarah.smith@examplerealty.com",
          "photo": "https://p.rdcpix.com/v01/listing_photo.jpg",
          "url": "https://www.realtor.com/realestateandhomes-detail/..."
        }
      ]
    }
  }
]
```

#### Key Fields

- **Identities**: `property_id`, `fulfillment_id` (Agent ID)
- **Specs**: `beds`, `baths`, `sqft`, `type`, `list_date`
- **Financials**: `list_price`, `sold_price`, `sold_date`
- **Location**: `address`, `city`, `state`, `zip`, `lat`, `lon`
- **Contact**: `agent_name`, `agent_phone`, `agent_email`, `office_name`

***

### 🚀 Use Cases

- **Market Research**: Track inventory levels and days on market in key cities.
- **Lead Generation**: Identify listing agents for partnership opportunities.
- **Alerting**: Get notified of new listings matching your specific criteria.
- **Valuation Models**: Ingest sold data to build accurate pricing models.

***

### 🛡️ Best Practices

- **Batching**: Group nearby cities to maximize efficiency.
- **Sorting**: Use `newest` for monitoring and `relevant` for general scraping.
- **Pagination**: Use higher `page_count` (10+) for deep market scrapes.

***

*Powered by Apify. Data you can trust.*

# Actor input Schema

## `cities` (type: `array`):

List of cities to fetch property listings from.

## `page_count` (type: `integer`):

How many pages to fetch per city.

## `property_type` (type: `string`):

Choose a specific property type or 'ANY' to include all.

## `sort_option` (type: `string`):

Select how the listings should be sorted (e.g., by price, date, or size).

## `status` (type: `string`):

Select listing status or ALL to include all.

## Actor input object example

```json
{
  "cities": [
    "Los Angeles"
  ],
  "page_count": 1,
  "property_type": "ANY",
  "sort_option": "relavant listings",
  "status": "for_sale"
}
```

# Actor output Schema

## `overview` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "cities": [
        "Los Angeles"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("propertyapi/realtor-property-data-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "cities": ["Los Angeles"] }

# Run the Actor and wait for it to finish
run = client.actor("propertyapi/realtor-property-data-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "cities": [
    "Los Angeles"
  ]
}' |
apify call propertyapi/realtor-property-data-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,propertyapi/realtor-property-data-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/EZxoRvuqj3jGrpTmN/builds/gdmHWcjU8SVjhK7mf/openapi.json