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Model Context Protocol (MCP) server for BatchData.io property and address APIs - Real estate data integration for Claude and other AI assistants
Configuration
View docs{
"mcpServers": {
"zellerhaus-batchdata-mcp-real-estate": {
"command": "node",
"args": [
"/path/to/batchdata-mcp-real-estate/batchdata_mcp_server.js"
],
"env": {
"BATCHDATA_API_KEY": "your_api_key_here"
}
}
}
}This MCP server provides direct access to BatchData real estate data through an MCP client, empowering you to verify addresses, geocode locations, and perform detailed property searches within natural language prompts and structured queries alike. It lets you integrate property and address data into your workflows with scalable, MCP-driven access.
You interact with BatchData MCP Real Estate just like other MCP endpoints: send requests for address verification, autocompletion, geocoding, and property queries, and receive structured results you can use in your applications or conversational flows. Start with address tasks such as verify-address, autocomplete-address, geocode-address, and reverse-geocode to validate locations and convert between addresses and coordinates. Then move to property operations like lookup-property, search-properties, search-properties-by-boundary, and count-properties to retrieve property details, perform advanced searches, and count results to gauge scope.
Use these capabilities to build property intelligence into your applications, from validating client-provided addresses to locating comparable properties within a chosen radius or geographic boundary. For environment-driven setups, provide your API key and run the local MCP server so your client can query BatchData via the MCP interface.
Prerequisites you need before installing: Node.js and npm (or yarn) installed on your machine.
1) Clone or download this MCP server to your machine.
2) Install dependencies.
npm install3) Configure your API key. Acquire your BatchData API key and set it in your environment or in the configuration shown below.
4) Build the TypeScript project.
npm run build5) Start the server locally to begin accepting MCP requests.
npm startIf you use Claude Desktop, configure the MCP server to run locally with your API key. The following configuration shows how to point Claude Desktop at the local MCP server instance.
{
"mcpServers": {
"batchdata": {
"command": "node",
"args": ["/path/to/batchdata-mcp-real-estate/batchdata_mcp_server.js"],
"env": {
"BATCHDATA_API_KEY": "your_api_key_here"
}
}
}
}You can run the server via Docker if you prefer containerized deployment. The Docker setup provides multi-stage builds, a non-root user, and health checks to ensure production readiness. Use Docker Compose for orchestration and view logs to monitor status.
Protect your API key and restrict access to trusted clients. Be mindful of API rate limits when performing address and property queries to avoid throttling.
Count properties within a defined area to estimate inventory, verify a mailing address before a real estate campaign, or retrieve detailed property data by APN for due diligence.
USPS address verification and standardization to ensure accuracy of mailing and location data.
Smart address suggestions as you type to improve data quality and user experience.
Convert a physical address into latitude/longitude coordinates for mapping and spatial queries.
Convert coordinates back into a readable address string for display or logging.
Retrieve detailed property information by address or APN for diligence and insights.
Advanced filtered search to find properties matching multiple criteria.
Geographic searches using bounding boxes or radius to locate properties within an area.
Lightweight query to count properties that meet specific criteria.