Weather MCP Server

A Python Model Context Protocol server that gives an AI current weather and forecasts. It geocodes locations and reads forecast data from Open-Meteo, then optionally uses Groq to explain the result naturally.

Requirements

• Python 3.11 or newer

• A Groq API key for AI-generated summaries

• Internet access for Open-Meteo and Groq requests

Related MCP server: Weather MCP Server

Setup

PowerShell:

py -3.11 -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install -e ".[dev]"
Copy-Item .env.example .env

Open .env and set GROQ_API_KEY. The server still works without the key, but it returns structured JSON instead of an AI summary.

Run

Browser UI

Start the user-facing weather chat:

python -m weather_mcp_server.web

Then open http://127.0.0.1:8000. Ask questions such as “Will it rain in London tomorrow?” The browser sends the question to the web adapter, which invokes the same get_weather tool exposed by the MCP server.

Run the server directly:

python -m weather_mcp_server.server

MCP clients can use the checked-in .vscode/mcp.json configuration. In VS Code, open this folder as the workspace, install the Python extension if prompted, and start the weather-mcp-server MCP server from the MCP controls.

The server exposes one tool:

• get_weather(location, forecast_days=3): returns current conditions and 1-7 days of forecast data.

Test

python -m pytest

The tests mock Open-Meteo, so they do not require network access or a Groq key.