MCP server for 7-day weather intelligence — rain, UV, heat & air quality with real SHAP explainability
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# Weather MCP MCP server that predicts rain for the next 7 days in any city and explains the prediction using SHAP values. Mirrors Part 3 of `weather_shap.ipynb`: **XGBoost + SHAP TreeExplainer + live Open-Meteo data**. ## Tools | Tool | Purpose | | --- | --- | | `predict_rain_7day` | 7-day rain probability forecast for a city. Trains an XGBoost model on 2 years of historical data on first call, then caches it. | | `explain_rain_prediction` | SHAP factors for a specific forecasted day — which feature pushed the probability up or down and by how much. | | `city_model_info` | Metadata about the cached model (accuracy, training window). | Data source: [Open-Meteo](https://open-meteo.com/) (no API key required). ## Install ```bash cd weather-mcp python -m venv .venv source .venv/bin/activate pip install -e . ``` This installs the `weather-mcp` console script, which is what the MCP clients below will launch. ## Running locally (smoke test) ```bash weather-mcp ``` The server speaks MCP over stdio — it will sit waiting for JSON-RPC. Use Ctrl-C to stop. Real testing happens through one of the clients below. ## Connect to Claude Desktop Edit `~/.config/Claude/claude_desktop_config.json` (Linux) or `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS): ```json { "mcpServers": { "weather": { "command": "/absolute/path/to/weather-mcp/.venv/bin/weather-mcp" } } } ``` Restart Claude Desktop. You should see a 🔌 icon listing `predict_rain_7day`, `explain_rain_prediction`, and `city_model_info`. ## Connect to Cursor Settings → MCP → Add new MCP server: - **Name:** `weather` - **Command:** `/absolute/path/to/weather-mcp/.venv/bin/weather-mcp` ## Connect to VS Code (Continue extension or any MCP-aware client) Add to your client's MCP config: ```json { "mcpServers": { "weather": { "command": "/absolute/path/to/weather-mcp/.venv/bin/weather-mcp", "args": [] } } } ``` ## Example conversation > **You:** …
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