measure-space

This MCP server provides a unified interface for Measure Space API services, including hourly and daily weather forecasts, climate data, air quality, agriculture metrics, pollen forecasts, and geocoding (city ↔ lat/lon and lat/lon ↔ city), along with timezone and astronomy data. To use it, choose the implementation you prefer: the Python version or the TypeScript version. Each implementation exposes the same MCP endpoints and follows the MCP protocol, returning model context data for requests such as weather forecasts, climate summaries, air quality readings, and geocoding lookups. Configure your environment with the appropriate API keys for the services you intend to use, then start the server. Clients can connect via MCP and request the relevant contexts using the provided service IDs and keys. The TypeScript build can be run with Node.js after building, while the Python version runs directly via the Python module.

Prerequisites:

• Python (3.8+), or Node.js (12+ or higher) for the TypeScript implementation
• Access to Measure Space API keys for the services you will query
• Git to clone the repository

Installation steps (Python implementation):

1. Install Python dependencies (from the python/ directory):
   • cd python/
   • python -m pip install -r requirements.txt
2. Configure environment variables with your API keys or create a .env file (see environment variables in mcp_config):
   • GEOCODING_API_KEY, HOURLY_WEATHER_API_KEY, DAILY_WEATHER_API_KEY, DAILY_CLIMATE_API_KEY, AIR_QUALITY_API_KEY, AGRICULTURE_API_KEY, POLLEN_API_KEY
3. Run the Python MCP server:
   • python -m measure_space_api.server

Installation steps (TypeScript implementation):

1. Install Node.js dependencies (from the typescript/ directory):
   • cdtypescript/
   • npm install
2. Build the TypeScript project (if a build step exists):
   • npm run build
3. Configure environment variables (same as above) and run the server:
   • node dist/server.js
4. Alternatively, use npm scripts if provided in package.json to start the server directly.

General notes:

• Ensure network access to Measure Space API endpoints and that your API keys are correctly configured.
• Use the mcp_config section to determine how to launch each implementation and supply env variables as shown.

Tips and caveats:

• The server requires separate API keys for each service; only enable the services you plan to use.
• If you encounter TLS or network errors, verify that your environment allows outbound connections to the Measure Space API endpoints.
• For containerized deployments, you can translate the mcp_config entries into docker run commands by embedding the env vars and mounting necessary volumes if needed.
• The TypeScript implementation exposes the same MCP endpoints as the Python one; choose the one that best fits your deployment stack.
• Typical MCP port defaults are 8080 or 3000 depending on the implementation—check your runtime logs to confirm the listening port.