# Realtor.com Property Scraper (`jungle_synthesizer/realtor-scraper`) Actor

Scrape property listings from Realtor.com. Extracts prices, beds, baths, sqft, address, agent, photos, and listing details for for-sale and recently-sold homes.

- **URL**: https://apify.com/jungle\_synthesizer/realtor-scraper.md
- **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community)
- **Categories:** Real estate
- **Stats:** 2 total users, 0 monthly users, 43.5% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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/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

## Realtor.com Property Listings Scraper

Scrapes for-sale and recently-sold property listings from [Realtor.com](https://www.realtor.com). Returns price, beds, baths, square footage, full address, property type, year built, HOA fees, days on market, listing agent and photos as structured JSON.

***

### Realtor.com Scraper Features

- Search any US market by city and state
- Switch between for-sale and recently-sold inventory
- Returns 23 fields per property, including agent name, phone and brokerage
- Captures HOA fee, lot size, garage and year built — the fields that decide a deal
- `days_on_market` on every record, for staleness analysis
- Photo URLs returned as an array
- Caps output with `maxItems` per location

***

### What can you do with Realtor.com listing data?

- **Investors** — Screen a market for price-per-square-foot outliers and long days-on-market, which is where negotiating room lives.
- **Appraisers and analysts** — Pull recently-sold comparables for a ZIP code instead of paging through them by hand.
- **Proptech products** — Seed a listings database with real inventory rather than licensing a feed.
- **Agent prospecting** — Build a contact list of listing agents active in a specific market.
- **Market reporting** — Track median price, inventory and days on market across cities over time.

***

### How Realtor.com Scraper Works

1. You supply a location in Realtor.com's own format — `San-Francisco_CA`, `Austin_TX`.
2. The scraper opens the matching search for the chosen `listingType`.
3. It walks the result pages and opens each property detail page for the full field set.
4. Records stream to the dataset as they are parsed, stopping at `maxItems` per location.

***

### Input

```json
{
  "location": "Austin_TX",
  "listingType": "for-sale",
  "maxItems": 100
}
```

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `location` | string | `San-Francisco_CA` | City and state, hyphenated city with underscore state — `San-Francisco_CA`, `Austin_TX` |
| `listingType` | string | `for-sale` | `for-sale` or `recently-sold` |
| `maxItems` | integer | `10` | Maximum property records per location |

Run it twice with the same location and both listing types to get asking prices and recent clearing prices side by side.

***

### Realtor.com Scraper Output Fields

```json
{
  "listing_id": "M1234567890",
  "listing_url": "https://www.realtor.com/realestateandhomes-detail/123-Main-St_Austin_TX_78701",
  "price": "$1,250,000",
  "beds": "4",
  "baths": "3",
  "sqft": "2450",
  "address": "123 Main St",
  "city": "Austin",
  "state": "TX",
  "zip_code": "78701",
  "listing_type": "for-sale",
  "property_type": "single_family",
  "year_built": "1998",
  "lot_size": "0.24 acres",
  "garage": "2 car attached",
  "hoa_fee": "$85",
  "days_on_market": "37",
  "agent_name": "Jane Doe",
  "agent_phone": "512-555-0100",
  "broker_name": "Austin Realty Group"
}
```

| Field | Type | Description |
|-------|------|-------------|
| `listing_id` | string | Realtor.com listing ID |
| `listing_url` | string | URL of the property detail page |
| `price` | string | Listing price, formatted — e.g. `$1,250,000` |
| `beds` | string | Number of bedrooms |
| `baths` | string | Number of bathrooms |
| `sqft` | string | Square footage |
| `address` | string | Full street address |
| `city` | string | City |
| `state` | string | State abbreviation |
| `zip_code` | string | ZIP code |
| `listing_type` | string | `for-sale` or `recently-sold` |
| `property_type` | string | e.g. `single_family`, `condo`, `townhouse` |
| `year_built` | string | Year the property was built |
| `lot_size` | string | Lot size in sqft or acres |
| `garage` | string | Garage / parking description |
| `hoa_fee` | string | HOA monthly fee, if applicable |
| `days_on_market` | string | Days the listing has been active |
| `agent_name` | string | Listing agent name |
| `agent_phone` | string | Listing agent phone number |
| `broker_name` | string | Brokerage name |
| `photo_urls` | array | Array of photo URLs |
| `description` | string | Property description text |
| `scraped_at` | string | ISO 8601 timestamp of extraction |

***

### FAQ

#### What location format does the Realtor.com Scraper expect?

Realtor.com's own: city hyphenated, state after an underscore. `San-Francisco_CA`, `New-York_NY`, `Austin_TX`.

#### Can I get sold prices rather than asking prices?

Yes. Set `listingType` to `recently-sold`. That is the closest public equivalent to transaction data on this source.

#### Does it need a Realtor.com account?

No. It reads public listing pages.

#### Why is `price` a formatted string instead of a number?

It is returned as the listing displays it, currency symbol and separators included, without a lossy cast. Strip and parse it where you control the rounding.

#### Can I search by ZIP code or draw a map area?

Not currently — search is by city and state. ZIP appears in the output, so filter after the fact if you need a specific one.

***

### Need More Features?

Want ZIP-level search or price-band filters? Open an issue on the actor.

### Why Use Realtor.com Scraper?

- **Sold comparables, not just listings** — `recently-sold` gives real clearing prices, which is what valuation work actually needs.
- **Agent contact on every record** — Name, phone and brokerage come standard, so the same pull serves prospecting and analysis.
- **Pay per property** — No subscription, no seat licence. A one-off market study costs what those records cost and then stops.

# Actor input Schema

## `sp_intended_usage` (type: `string`):

What will this data feed? E.g. lead lists, KYB checks, price tracking.

## `sp_improvement_suggestions` (type: `string`):

Provide any feedback or suggestions for improvements.

## `sp_contact` (type: `string`):

We'll personally help with your use case. No spam.

## `resumeCursor` (type: `string`):

Leave empty for a fresh crawl. To CONTINUE a previous run where it stopped — without paying again for records you already received — paste the `resumeCursor` value from that run's Output (the run's OUTPUT key). Resume promptly: the previous run's data expires with your account's retention window (free tier: your ~10 most recent runs).

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

City and state to search (e.g., "San-Francisco\_CA", "Austin\_TX")

## `listingType` (type: `string`):

Type of listings to scrape

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

Maximum number of property records to scrape (per location)

## Actor input object example

```json
{
  "sp_intended_usage": "Describe your intended use...",
  "sp_improvement_suggestions": "Share your suggestions here...",
  "sp_contact": "Share your email here...",
  "location": "San-Francisco_CA",
  "listingType": "for-sale",
  "maxItems": 10
}
```

# Actor output Schema

## `results` (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 = {
    "sp_intended_usage": "Describe your intended use...",
    "sp_improvement_suggestions": "Share your suggestions here...",
    "sp_contact": "Share your email here...",
    "location": "San-Francisco_CA",
    "maxItems": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("jungle_synthesizer/realtor-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 = {
    "sp_intended_usage": "Describe your intended use...",
    "sp_improvement_suggestions": "Share your suggestions here...",
    "sp_contact": "Share your email here...",
    "location": "San-Francisco_CA",
    "maxItems": 10,
}

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

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

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

```

## CLI example

```bash
echo '{
  "sp_intended_usage": "Describe your intended use...",
  "sp_improvement_suggestions": "Share your suggestions here...",
  "sp_contact": "Share your email here...",
  "location": "San-Francisco_CA",
  "maxItems": 10
}' |
apify call jungle_synthesizer/realtor-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=jungle_synthesizer/realtor-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/0Urfqim8hEPpdwHHt/builds/sYPX47hSiS5IsqhpS/openapi.json