MLS API Python Client

Extract MLS data with our MLS API Python client. Get programmatic access to GPS coordinates, structured JSON data, rent and sale offers, deduplication across platforms, Rightmove, Apartments.com, Zumper, Realtor, property listings from Zillow, and more using simple Python code. Start free, no credit card required.

Try MLS API Python Client

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Integrate our MLS API

The Apify API client for Python is the official library that allows you to use MLS API in Python, providing convenience functions and automatic retries on errors. Get started with simple pip installation and robust error handling built-in.

Python

JavaScript

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = { "location": "New York, NY" }
9
10# Run the Actor and wait for it to finish
11run = client.actor("tri_angle/real-estate-aggregator").call(run_input=run_input)
12
13# Fetch and print Actor results from the run's dataset (if there are any)
14print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
15for item in client.dataset(run["defaultDatasetId"]).iterate_items():
16    print(item)
17
18# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

MLS API

MLS API in JavaScript

MLS MCP server

MLS API in CLI

Get data with MLS API Python client

Use our Python API client to extract real estate data by providing location (city, zip code, or address), offer types (rent/sale), selected providers, and maximum results per provider. The API returns structured data, including property details with prices, GPS coordinates, bedrooms, bathrooms, living area, photos, and platform-specific metadata in JSON format.

Input

{
 "units": "metric",
 "location": "New York, NY",
 "providers": [
  "apartments",
  "realtor",
  "zumper",
  "zillow",
  "rightmove"
 ],
 "offerTypes": [
  "sale",
  "rent"
 ],
 "deduplicateResults": true,
 "maxResultsPerProvider": 20
}

Output

{
 "gps": {
  "lat": 43.291458,
  "lng": -73.578072
 },
 "zip": "12839",
 "city": "New York",
 "urls": {
  "realtor": "<https://www.realtor.com/realestateandhomes-detail/31-33-Thomas-Ave_New-York_NY_12839_M93244-31969>"
 },
 "price": 420000,
 "state": "NY",
 "county": "Washington",
 "street": "31-33 Thomas Ave",
 "country": "United States",
 "localId": {
  "realtor": "2976460521"
 },
 "bedrooms": 6,
 "landArea": 6879.4308,
 "pictures": {
  "realtor": [
   "<https://ap.rdcpix.com/image1.jpg>",
   "<https://ap.rdcpix.com/image2.jpg>"
  ]
 },
 "bathrooms": 3,
 "offerType": "sale",
 "providers": [
  "realtor"
 ],
 "livingArea": 6.9,
 "priceCurrency": "USD",
 "realEstateType": {
  "realtor": "multi_family"
 }
}

How to use MLS API

Sign up for Apify account01

Creating an account is quick and free — no credit card required. Your account gives you access to more than 5,000 scrapers and APIs.

Get started for free

Install Apify Python client02

Install the Apify Python client using pip: pip install apify-client. This package provides a simple interface to interact with MLS API from your Python applications.

Get your Apify API token03

Go to settings in the Apify console and navigate to the “API & Integrations” tab. There, create a new token and save it for later.

Integrate MLS API04

Navigate to the MLS API page and click on the API dropdown menu in the top right corner. In the dropdown menu, you can see API clients, API endpoints, and more. Use the provided Python code examples to integrate MLS API into your Python application.

Open MLS Python API

Get your MLS data via API05

The MLS API returns structured JSON data that works perfectly with pandas, NumPy, and other Python data analysis libraries.

Why use Apify?

Never get blocked

Every plan (free included) comes with Apify Proxy, which is great for avoiding blocking and giving you access to geo-specific content.

Customers love us

We truly care about the satisfaction of our users and thanks to that we're one of the best-rated data extraction platforms on both G2 and Capterra.

Monitor your runs

With our latest monitoring features, you always have immediate access to valuable insights on the status of your web scraping tasks.

Export to various formats

Your datasets can be exported to any format that suits your data workflow, including Excel, CSV, JSON, XML, HTML table, JSONL, and RSS.

Integrate Apify to your workflow

You can integrate your Apify runs with platforms such as Zapier, Make, Keboola, Google Drive, or GitHub. Connect with practically any cloud service or web app.

Large developer community

Apify is built by developers, so you'll be in good hands if you have any technical questions. Our Discord server is always here to help!

Python-ready MLS data extraction

Connect to hundreds of apps right away using ready-made integrations, or set up your own with webhooks and our API.

Frequently asked questions

No, there is no official MLS Python API. However, this Apify Actor provides a unified Python API client interface that aggregates data from multiple real estate platforms (Zillow, Realtor, Zumper, Apartments.com, and Rightmove) into a single, standardized format, effectively creating a comprehensive real estate data Python API client.

Yes, you can try the Real Estate Aggregator Python API client for free. Apify offers free credits to new users, and the Actor uses pay-per-event pricing starting at $0.003 per Actor start and $0.002 per extracted listing. You can test the functionality before committing to larger usage.

The Python MLS API client provides comprehensive property data including prices, GPS coordinates, addresses, bedrooms and bathrooms count, living area and land area measurements, property photos, real estate type classifications, local property IDs, offer types (rent/sale), and platform-specific metadata from Zillow, Realtor, Zumper, Apartments.com, and Rightmove.

Yes, it is legal to scrape MLS data using this Python API client. The client accesses publicly available property listings from MLS platforms. However, you should always comply with the terms of service of the MLS platforms being accessed and use the data responsibly for legitimate purposes like market research or property analysis.

Getting started with our MLS Python API is easy — simply create a free Apify account, get your API token, and start using the MLS API in Python, JavaScript, CLI, cURL, OpenAPI, or MCP.