# Realtor Scraper (`one_house/realtor-com-scraper`) Actor

Scrape for-sale, for-rent, and sold property listings from realtor.com by location.

- **URL**: https://apify.com/one\_house/realtor-com-scraper.md
- **Developed by:** [One House](https://apify.com/one_house) (community)
- **Categories:** Real estate, Lead generation, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 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.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#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

Extract for-sale, for-rent, and recently-sold property listings from [realtor.com](https://www.realtor.com) by location — price, beds, baths, square footage, address, coordinates, photos, and broker.

### What you get

- Address, city, state, ZIP, county, coordinates
- Price (list price, or sold price + sold date for recently-sold)
- Beds, baths, square footage, lot size, year built, stories, garage
- Listing status, list date
- Primary photo and photo count
- Broker/brokerage name
- Full raw API result for anything not mapped to a named field

With **Include full listing details** enabled, each listing also gets one extra request for:

- Full free-text description
- Price per square foot (for-sale/sold)
- Separate full/half bath counts
- Listing agent name, email, phone, and office (when the listing has one — builder/community listings often don't)
- Pet policy text (rentals)

### How to use

1. Open this Actor and click **Start**
2. Set **Location** (e.g. `Austin, TX`) — same free-text format realtor.com's own search box accepts
3. Pick **Mode**: `BUY`, `RENT`, or `SOLD`
4. Optionally set **Min/max price** and **Min/max beds** — these are applied server-side by realtor.com, not filtered after the fact
5. Set **Max items** to cap how many listings are returned (0 = all matching listings)
6. Optionally enable **Include full listing details** for full description, agent contact, and price per sqft — one extra request per listing, so it's off by default
7. Run and download results from the **Dataset** tab

### Input example

```json
{
  "location": "Austin, TX",
  "mode": "BUY",
  "minPrice": 250000,
  "minBeds": 3,
  "maxItems": 100
}
```

### Output example

```json
{
  "propertyId": "8838103763",
  "url": "https://www.realtor.com/realestateandhomes-detail/11000-Anderson-Mill-Rd-Unit-11_Austin_TX_78750_M88381-03763",
  "status": "for_sale",
  "price": 299000,
  "address": "11000 Anderson Mill Rd Unit 11",
  "city": "Austin",
  "state": "TX",
  "postalCode": "78750",
  "county": "Williamson",
  "latitude": 30.450886,
  "longitude": -97.814795,
  "beds": 3,
  "baths": 2.5,
  "sqft": 1382,
  "yearBuilt": 2001,
  "primaryPhoto": "https://ap.rdcpix.com/...",
  "brokerName": "Compass RE Texas LLC - Austin",
  "source": "realtor.com",
  "scrapedAt": "2026-08-08T00:00:00.000Z"
}
```

### Tips

- Start with a small `maxItems` to confirm results look right before scaling up.
- `minPrice`/`maxPrice`/`minBeds`/`maxBeds` are applied by realtor.com's own search, so they don't cost extra requests the way client-side filtering would.
- For `SOLD` mode, `price` is often `null` for older sales — check `soldDate`/`soldPrice` instead.

# Actor input Schema

## `location` (type: `string`):

City and state (e.g. "Austin, TX") or ZIP code, in the same free-text format realtor.com's own search box accepts.

## `mode` (type: `string`):

Listing type to search for.

## `minPrice` (type: `integer`):

Optional minimum list price filter (e.g. 250000).

## `maxPrice` (type: `integer`):

Optional maximum list price filter (e.g. 750000).

## `minBeds` (type: `integer`):

Optional minimum bedroom count filter.

## `maxBeds` (type: `integer`):

Optional maximum bedroom count filter.

## `maxItems` (type: `integer`):

Maximum number of listings to return. Set 0 for all matching listings.

## `pageSize` (type: `integer`):

Listings fetched per API request (1-200).

## `includeDetails` (type: `boolean`):

Fetch each listing's own detail page data too (full description, agent contact, price per sqft, pet policy for rentals). One extra request per listing.

## Actor input object example

```json
{
  "location": "Austin, TX",
  "mode": "BUY",
  "maxItems": 100,
  "pageSize": 42,
  "includeDetails": false
}
```

# 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 = {
    "location": "Austin, TX",
    "maxItems": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("one_house/realtor-com-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 = {
    "location": "Austin, TX",
    "maxItems": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("one_house/realtor-com-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 '{
  "location": "Austin, TX",
  "maxItems": 100
}' |
apify call one_house/realtor-com-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,one_house/realtor-com-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/URPXCUWje4JkG4QBm/builds/bmX6GmlHHxH039Tk4/openapi.json