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Zillow Real Estate Data

Zillow Real Estate Data

Local
github.com/sap156Data & Analytics56Updated 77w ago

About Zillow Real Estate Data

A Zillow real estate data MCP server built with Python and FastMCP. It is intended for users who need property listings, valuations, and market information through an MCP client. It also includes a mortgage calculator and runs over stdio or HTTP.

Key features

  1. 01Property search by location and price
  2. 02Property details and Zestimate lookup
  3. 03Market trends for a given location
  4. 04Mortgage payment calculation with cost inputs
  5. 05Stdio and HTTP run modes

Use cases

  1. 01Searching for listings in a city within a price range
  2. 02Looking up Zestimate values for specific addresses
  3. 03Estimating monthly mortgage payments for different down payments

MCP support

The server exposes Zillow property data to MCP clients through tools such as search_properties and resources under the zillow:// scheme.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"zillow": {
"command": "npx",
"args": [
"-y",
"zillow-mcp-server"
],
"env": {
"ZILLOW_API_KEY": "<ZILLOW_API_KEY>"
}
}
}
}
Run commandnpx -y zillow-mcp-server
Environment variables to set
ZILLOW_API_KEYSecret

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmzillow-mcp-server

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Zillow MCP Server

A Model Context Protocol (MCP) server that provides real-time access to Zillow real estate data, built with Python and FastMCP.

Features

  • 🏠 Property Search: Search for properties by location, price range, and property features
  • 💰 Property Details: Get detailed information about specific properties
  • 📊 Zestimates: Access Zillow's proprietary home valuation data
  • 📈 Market Trends: View real estate market trends for any location
  • 🧮 Mortgage Calculator: Calculate mortgage payments based on various inputs
  • 🔍 Health Check: Verify API connectivity and monitor performance

Installation

Prerequisites
Setup
  1. Clone this repository:

    git clone https://github.com/yourusername/zillow-mcp-server.git
    cd zillow-mcp-server
    
  2. Install the dependencies:

    pip install -r requirements.txt
    
  3. Create a .env file with your Zillow API key:

    ZILLOW_API_KEY=your_zillow_api_key_here
    
Running the Server

Run the server with options:

# Standard stdio mode (for Claude Desktop)
python zillow_mcp_server.py

# HTTP server mode (for remote access)
python zillow_mcp_server.py --http --port 8000

# Debug mode for more verbose logging
python zillow_mcp_server.py --debug
Docker Deployment

You can also run the server using Docker:

# Build the Docker image
docker build -t zillow-mcp-server .

# Run with environment variables
docker run -p 8000:8000 -e ZILLOW_API_KEY=your_key_here zillow-mcp-server

# Or using an env file
docker run -p 8000:8000 --env-file .env zillow-mcp-server

Usage with Claude Desktop

Add the Zillow MCP server to your Claude Desktop configuration file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "zillow": {
      "command": "python",
      "args": ["/path/to/zillow_mcp_server.py"]
    }
  }
}

For remote HTTP server:

{
  "mcpServers": {
    "zillow-remote": {
      "command": "npx",
      "args": ["mcp-remote", "https://your-mcp-server-url.com/sse"]
    }
  }
}

Available Tools

Search Properties

Search for properties based on various criteria:

search_properties(
    location: str,
    type: str = "forSale",
    min_price: Optional[int] = None,
    max_price: Optional[int] = None,
    beds_min: Optional[int] = None,
    beds_max: Optional[int] = None,
    baths_min: Optional[float] = None,
    baths_max: Optional[float] = None,
    home_types: Optional[List[str]] = None
)

Example usage in Claude:

Please search for properties in Seattle with prices between $500,000 and $800,000.
Get Property Details

Get detailed information about a specific property:

get_property_details(
    property_id: str = None,
    address: str = None
)

Example usage in Claude:

Can you get the details for the property with ID 12345?
Get Zestimate

Get Zillow's estimated value for a property:

get_zestimate(
    property_id: str = None,
    address: str = None
)

Example usage in Claude:

What's the Zestimate for 123 Main St, Seattle, WA?
Get Market Trends

Get real estate market trends for a specific location:

get_market_trends(
    location: str,
    metrics: List[str] = ["median_list_price", "median_sale_price", "median_days_on_market"],
    time_period: str = "1year"
)

Example usage in Claude:

What are the current real estate trends in Boston over the past year?
Calculate Mortgage

Calculate mortgage payments and related costs:

calculate_mortgage(
    home_price: int,
    down_payment: int = None,
    down_payment_percent: float = None,
    loan_term: int = 30,
    interest_rate: float = 6.5,
    annual_property_tax: int = None,
    annual_homeowners_insurance: int = None,
    monthly_hoa: int = 0,
    include_pmi: bool = True
)

Example usage in Claude:

Calculate the monthly mortgage payment for a $600,000 house with 20% down and a 6% interest rate.
Check Health

Verify the Zillow API connection and get server status:

check_health()

Example usage in Claude:

Please check if the Zillow API is currently responsive.
Get Server Tools

Get a list of all available tools on this server:

get_server_tools()

Example usage in Claude:

What tools are available in the Zillow MCP server?

Available Resources

Property Resource

Get property information as a formatted text resource:

zillow://property/{property_id}
Market Trends Resource

Get market trends information as a formatted text resource:

zillow://market-trends/{location}

Error Handling

The server implements robust error handling with:

  • Automatic retries with exponential backoff
  • Detailed error logging
  • Rate limit handling
  • Connection timeouts
  • Graceful degradation

Technical Architecture

This MCP server is built using:

  • FastMCP: A Pythonic framework for building Model Context Protocol servers
  • Requests: For making HTTP requests to the Zillow Bridge API with connection pooling and retries
  • Backoff: For implementing exponential backoff retry logic
  • python-dotenv: For managing environment variables

The server provides both tools (interactive functions) and resources (static data) that Claude can access to provide real estate information to users.

Limitations and Considerations

  • Zillow's API has usage limits (typically 1,000 requests per day per dataset)
  • Zillow's terms of service prohibit storing data locally; all requests must be dynamic
  • You must properly attribute data to Zillow in the user interface
  • The Bridge API format may change; refer to Zillow's documentation for updates

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature-name
  3. Commit your changes: git commit -m 'Add some feature'
  4. Push to the branch: git push origin feature-name
  5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

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