Yatmo neighbourhood data for real estate

Real estate neighbourhood data: nearest school, shops, transport with travel times, 25 countries.

OtherPythonv1.0.1

Yatmo MCP server: neighbourhood data for AI assistants and agents

Yatmo exposes its neighbourhood intelligence to AI clients through a remote MCP server. Connect Claude, Cursor, VS Code or your own agent, and it can answer "what is around this property?" with real data: nearest school, nursery, supermarket, public transport, train station, motorway access, distances with travel times, and a quotable summary paragraph, in 25 countries.

This repository holds ready-to-copy client configurations and a dependency-free quick start. The server itself is operated by Yatmo at https://mcp.yatmo.com/mcp/v1 (Streamable HTTP). Full documentation: documentation.yatmo.com/mcp.

The four tools

ToolReturns
yatmo_get_location_summaryA human-readable neighbourhood paragraph plus the nearest school, nursery, supermarket, transport and the reverse-geocoded place
yatmo_get_nearby_poisAn ordered list of points of interest around a property, optionally filtered by category, within a radius
yatmo_get_nearest_by_categoryThe single nearest place of a category, with distance and travel time
yatmo_get_accessibility_profilePublic-transport presence, nearest stop, nearest train station, nearest motorway access

All tools take latitude, longitude, country (BE, FR, UK...) and language, and return the same envelope: text (a summary the assistant can quote), facts (structured data), warnings and metadata. Categories use one vocabulary everywhere: school, nursery, supermarket, public_transport, train_station, motorway. Details: tools reference.

Authentication

Every request carries your Yatmo backend key in the LicenceKey header (LicenseKey is accepted too). Keep the key in the client's secret store, never in a public web page: the key grants access to your Yatmo account. Get a key at yatmo.com; keys explained.

Connect a client

Generic remote-MCP configuration (configs/mcp.json), accepted by most clients, sometimes under a slightly different parent key:

{
  "mcpServers": {
    "yatmo": {
      "url": "https://mcp.yatmo.com/mcp/v1",
      "headers": { "LicenceKey": "YOUR_KEY" }
    }
  }
}

Claude.ai and Claude Desktop: Settings > Connectors > Add custom connector, URL https://mcp.yatmo.com/mcp/v1, custom header LicenceKey: YOUR_KEY. The four tools appear once the connector is enabled.

Claude Code:

claude mcp add --transport http yatmo https://mcp.yatmo.com/mcp/v1 --header "LicenceKey: YOUR_KEY"

Cursor: copy configs/cursor/mcp.json to .cursor/mcp.json in your project (or to ~/.cursor/mcp.json for every project).

VS Code (Copilot agent mode): copy configs/vscode/mcp.json to .vscode/mcp.json.

Your own agent (Anthropic, OpenAI or any LLM SDK): use an MCP client library (TypeScript, Python, .NET, Go) with the Streamable HTTP transport, add the LicenceKey header to the transport, and forward the four tool definitions to the model. quickstart.py shows the raw protocol without any library.

Try it from the command line

export YATMO_KEY=your_backend_key
python3 quickstart.py          # initialize, list the tools, call yatmo_get_location_summary on a Brussels address
sh quickstart.sh               # the same three calls with curl

Prompts that work well

  • "What is the neighbourhood like around 50.8467, 4.3525 in Belgium? Answer in French."
  • "Nearest primary school and supermarket to this listing, with travel times on foot."
  • "Is this address well served by public transport? Nearest train station and motorway access?"
  • "List the points of interest within 800 m of the property, schools and supermarkets only."

The assistant answers from the text and facts of the tools; distances come with the mode they were measured in.

More

MIT licence for the files of this repository. Yatmo is a paid service for real estate portals, agency networks and developers.

Directories

The server is published in the official MCP registry as com.yatmo/yatmo (server.json in this repository) and submitted to the Docker MCP Catalog, Smithery and mcp.so. In clients that read the registry, search for "yatmo" or "real estate".

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
npx -y @yatmo/mcp

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "com-yatmo-yatmo": {
      "command": "npx",
      "args": [
        "-y",
        "@yatmo/mcp"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

@yatmo/mcpnpm

Compatible MCP Clients

Yatmo neighbourhood data for real estate works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

Learn More