# Realtor.com Property Scraper (`one-api/realtor-property-scraper`) Actor

Scrape Realtor.com listings, full property details, agents, mortgages, and autocomplete suggestions. Search by location/ZIP/coordinates/polygon/URL with full filter set. Contact: oneapi.project@gmail.com

- **URL**: https://apify.com/one-api/realtor-property-scraper.md
- **Developed by:** [ONE API](https://apify.com/one-api) (community)
- **Categories:** Real estate, Lead generation
- **Features:** Limited permissions
- **Stats:** 63 total users, 24 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $7.00 / 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.
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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Realtor.com Property Scraper

Scrape **Realtor.com** listings, full property details, agent info, mortgage estimates, and search-box autocomplete suggestions — all from one Actor. Backed by [realtyapi.io](https://realtyapi.io)'s real-time Realtor API.

⭐️ Found this useful? Please leave 5 stars! Issues / requests: 📬 **support@realtyapi.io**

***

### What you can do

| Section | What it does | Input format |
|---|---|---|
| 🏠 **Property Details** | Full details for a specific listing | `property_id` digits, Realtor.com listing URL, or full street address — auto-detected per row |
| 🔎 **Search Listings** | Paginated search with filters | location string, ZIP, `lat,lng,radius_mi`, polygon (`lon lat,lon lat,...`), or Realtor.com search URL |
| 🔍 **Autocomplete** | Search-box suggestions (cities, ZIPs, neighborhoods, schools, addresses) | partial query string |
| 👤 **Agent Lookup** | Agent name, office, profile URL | `fulfillment_id` (found in any details/search response under `advertisers[].fulfillment_id`) |
| 💰 **Mortgage Calculator** | Monthly payment + breakdown | `price` or `price,downPayment,rate,term` |

You can fill any combination of sections in a single run — leave the others empty.

***

### Output

Each listing / property / agent / mortgage / autocomplete suggestion is pushed as **one dataset row**, flattened to friendly columns plus a `Raw` column with the original JSON.

| Mode | Input Given | Property ID | Status | Price | Beds | Baths | Sqft | Street | City | State | Zip | Agent Name | Listing URL | Raw |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| `search/bylocation` | Austin, TX (p1) | 8873523070 | for_sale | 588888 | 3 | 2.5+ | 3066 | 13902 Panorama Dr | Austin | TX | 78732 | Elena Licari | https://www.realtor.com/... | `{...}` |
| `details/byid` | 8955838462 | 8955838462 | for_sale | 240000 | 3 | 2.5 | 1193 | 9504 Quail Village Ln | Austin | TX | 78758 | Carolina Aceituno | https://www.realtor.com/... | `{...}` |

Plus: `Listing ID`, `Lot Sqft`, `Year Built`, `Property Type`, `Latitude`, `Longitude`, `Days on Market`, `List Date`, `Photos` (cover URL), `Photo Count`, `Agent Fulfillment ID`, `Office Name`.

For nested/large fields (full photo arrays, schools, tax history, all phones, etc.) the complete upstream JSON is in the `Raw` column.

***

### Sample input

```json
{
    "property_inputs": [
        "8955838462",
        "https://www.realtor.com/realestateandhomes-detail/9504-Quail-Village-Ln_Austin_TX_78758_M89558-38462",
        "166 W 22nd St Unit 1D, New York, NY 10011"
    ],
    "search_inputs": ["Austin, TX", "78758", "30.4108,-97.7177,2"],
    "searchType": "For_Sale",
    "propertyType": "House,Condo",
    "priceRange": "min:300000,max:900000",
    "bedsRange": "min:2",
    "sortOrder": "Newest",
    "pages": 2,
    "resultCount": 50,

    "autocomplete_inputs": ["Brooklyn"],
    "agent_inputs": ["472555"],
    "mortgage_inputs": ["525000", "525000,105000,0.065,30"]
}
```

***

### Search filters (apply to all `search_inputs`)

- **searchType** — `For_Sale` | `For_Rent` | `Sold` (or comma-combined like `For_Sale,Sold`)
- **propertyType** — comma list of `House, Condo, Townhome, Multi_Family, Mobile, Farm, Land, Co-op`
- **priceRange / bedsRange / bathsRange / sqftRange** — `min:X` | `max:Y` | `min:X,max:Y` (baths support `2.5`)
- **sortOrder** — `Recommended`, `Newest`, `Oldest`, `Price_High_to_Low`, `Price_Low_to_High`, `Square_Feet`, `Lot_Size`, `Beds`, `Baths`, `Most_Recently_Sold`, `Open_House_Date`
- **pages** — how many pages to fetch (1–50). Each page = `resultCount` listings.
- **resultCount** — 1–200 per page, default 50
- **newConstruction / foreclosure** — `any` | `true` (only) | `false` (exclude)
- **openHouse** — `true` to keep only listings with an upcoming open house
- **keywords** — free-text, comma-separated (e.g. `pool,fireplace,granite countertops`)
- **daysOnMarketMax** — only listings within last N days

Filters apply to **every** `search_inputs` row in the run.

***

### Pricing

**Pay per result** — you only pay for dataset items the Actor pushes. Failed inputs return a row with `Status: ERROR: ...` and are billed the same as a successful row.

To cap spend, set `Max paid dataset items` on the run page.

***

### Tips

- **Need just one property?** Use the `property_inputs` section — auto-detects `property_id`, URL, or address.
- **Pull all listings in a city?** Use `search_inputs: ["City, ST"]` and crank `pages` (each page is up to 200 results).
- **Use a lat/lng circle?** Format: `30.4108,-97.7177,2` (last value is radius in miles).
- **Polygon?** `lon lat,lon lat,lon lat,...` — note longitude first (GeoJSON convention).
- **Resolve a Realtor.com URL?** Drop a search or detail URL straight into the matching section — both `byurl` modes parse the URL into the right call internally.

# Actor input Schema

## `property_inputs` (type: `array`):

Auto-detects each entry: digits → property_id, http(s) URL → listing URL, anything else → address. Each row = 1 property detail call.

## `search_inputs` (type: `array`):

Auto-detects each entry. Examples:
• `Austin, TX` (location)
• `78758` (ZIP)
• `30.4108,-97.7177,2` (lat,lng,radius_miles)
• `-97.74 30.40,-97.70 30.40,-97.70 30.43,-97.74 30.43` (polygon, lon-lat pairs)
• `https://www.realtor.com/realestateandhomes-search/Austin_TX/...` (search URL)

Filters below apply to every search. Each LISTING is pushed as one dataset item.

## `searchType` (type: `string`):

For_Sale (default) | For_Rent | Sold. Comma-separated for multi (e.g. `For_Sale,Sold`).

## `propertyType` (type: `string`):

Comma-separated. Leave empty for all. Allowed: House, Condo, Townhome, Multi_Family, Mobile, Farm, Land, Co-op

## `priceRange` (type: `string`):

`min:500000`, `max:1500000`, or `min:500000,max:1500000`

## `bedsRange` (type: `string`):

`min:3`, `max:5`, `min:3,max:5` (studio = `min:0`)

## `bathsRange` (type: `string`):

Decimals supported: `min:2`, `max:3.5`, `min:2,max:3.5`

## `sqftRange` (type: `string`):

`min:1000`, `max:3000`, `min:1000,max:3000`

## `sortOrder` (type: `string`):

How to sort search results. Default: Recommended (Realtor.com's relevance bucket).

## `pages` (type: `integer`):

1-based. Each page = up to `Result Count` listings.

## `resultCount` (type: `integer`):

Min 1, Max 200. Default 50.

## `newConstruction` (type: `string`):

Filter new-construction listings.

## `foreclosure` (type: `string`):

Filter foreclosure listings.

## `openHouse` (type: `boolean`):

Only listings with an upcoming open house (For_Sale).

## `keywords` (type: `string`):

Comma-separated amenities (e.g. `pool,fireplace,granite countertops`).

## `daysOnMarketMax` (type: `integer`):

Only listings within last N days. Empty = no limit.

## `autocomplete_inputs` (type: `array`):

Realtor.com search-box suggestions: cities, ZIPs, neighborhoods, addresses, schools, etc.

## `agent_inputs` (type: `array`):

Pulled from `listing_advertiser.fulfillment_id` in any details/search response.

## `mortgage_inputs` (type: `array`):

Required: price. Optional: downPayment ($), rate (decimal e.g. 0.065), term (years). Defaults: 20% down, 6.5%, 30yr.

## Actor input object example

```json
{
  "property_inputs": [
    "8955838462",
    "https://www.realtor.com/realestateandhomes-detail/9504-Quail-Village-Ln_Austin_TX_78758_M89558-38462",
    "166 W 22nd St Unit 1D, New York, NY 10011"
  ],
  "search_inputs": [
    "Austin, TX"
  ],
  "searchType": "For_Sale",
  "propertyType": "",
  "priceRange": "",
  "bedsRange": "",
  "bathsRange": "",
  "sqftRange": "",
  "sortOrder": "Recommended",
  "pages": 1,
  "resultCount": 50,
  "newConstruction": "any",
  "foreclosure": "any",
  "openHouse": false,
  "keywords": ""
}
```

# 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 = {
    "property_inputs": [
        "8955838462",
        "https://www.realtor.com/realestateandhomes-detail/9504-Quail-Village-Ln_Austin_TX_78758_M89558-38462",
        "166 W 22nd St Unit 1D, New York, NY 10011"
    ],
    "search_inputs": [
        "Austin, TX"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("one-api/realtor-property-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 = {
    "property_inputs": [
        "8955838462",
        "https://www.realtor.com/realestateandhomes-detail/9504-Quail-Village-Ln_Austin_TX_78758_M89558-38462",
        "166 W 22nd St Unit 1D, New York, NY 10011",
    ],
    "search_inputs": ["Austin, TX"],
}

# Run the Actor and wait for it to finish
run = client.actor("one-api/realtor-property-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 '{
  "property_inputs": [
    "8955838462",
    "https://www.realtor.com/realestateandhomes-detail/9504-Quail-Village-Ln_Austin_TX_78758_M89558-38462",
    "166 W 22nd St Unit 1D, New York, NY 10011"
  ],
  "search_inputs": [
    "Austin, TX"
  ]
}' |
apify call one-api/realtor-property-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,one-api/realtor-property-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/WhPhQWmuUTwEtyRge/builds/G5d7U6OICNpzae4du/openapi.json