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Weather MCP Server

Weather MCP Server

A Model Context Protocol (MCP) server that provides weather forecasts and alerts using the National Weather Service API.

Built following the official Model Context Protocol server development guide

Quick Start (Mac/Linux)

1. Clone and Setup

# Clone the repository to your preferred location git clone <repository-url> ~/weather-mcp cd ~/weather-mcp # Check the project structure ls -la # You should see: main.py, weather.py, pyproject.toml, README.md, etc.

2. Configure MCP Client

Add this configuration to your MCP client (e.g., Gemini CLI, Claude Desktop, etc.):

{ "mcpServers": { "weather": { "command": "uv", "args": [ "--directory", "~/weather-mcp", "run", "weather.py" ] } } }

Important: Replace ~/weather-mcp with the actual path where you cloned the repository. For example:

  • If you cloned to your home directory: "/home/yourusername/weather-mcp"
  • If you cloned to a projects folder: "/home/yourusername/projects/weather-mcp"

3. Monitor Server Activity

The server logs all activity to help you understand what's happening:

# Navigate to your cloned repository cd ~/weather-mcp # Watch server logs in real-time tail -f weather_mcp.log

Keep this terminal open while using the MCP server to see real-time logs of weather requests, API calls, and any errors.

How It Works

This MCP server acts as a bridge between your AI client and the National Weather Service API:

  1. Your AI client sends requests to the MCP server via stdio
  2. The MCP server processes requests and makes API calls to weather.gov
  3. Weather data is returned to your AI client in a structured format
  4. All activity is logged to weather_mcp.log for debugging and monitoring

Features

  • Weather Forecasts: Get detailed weather forecasts for any location using latitude/longitude coordinates
  • Weather Alerts: Retrieve active weather alerts for any US state
  • Server Information: Get details about the server configuration and capabilities
  • Comprehensive Logging: Built-in logging to both console and file with progress reporting

Development Setup

Prerequisites

  • Python 3.11+ installed
  • uv package manager (install uv)

Local Development

# 1. Clone the repository (if not already done) git clone <repository-url> ~/weather-mcp-dev cd ~/weather-mcp-dev # 2. Install dependencies uv sync # 3. Test the server locally uv run python weather.py # 4. In another terminal, monitor logs tail -f weather_mcp.log

Making Changes

  1. Edit the code: Modify weather.py or other files as needed
  2. Test your changes: Run uv run python weather.py to test locally
  3. Check logs: Monitor weather_mcp.log for any issues
  4. Update your MCP client: Restart your MCP client to pick up changes

Project Structure

weather-mcp/ ├── weather.py # Main MCP server implementation ├── main.py # Alternative entry point ├── pyproject.toml # Project configuration and dependencies ├── weather_mcp.log # Server logs (created when running) ├── LOGGING.md # Detailed logging documentation └── README.md # This file

Testing Tools

Once the server is running in your MCP client, you can test these tools:

get_forecast(latitude: float, longitude: float)

Get a detailed weather forecast for a specific location.

Example:

get_forecast(40.7128, -74.0060) # New York City
get_alerts(state: str)

Get active weather alerts for a US state (2-letter state code).

Example:

get_alerts("CA") # California alerts
server_info()

Get information about the server configuration and capabilities.

Configuration Details

The server uses the National Weather Service API with these settings:

  • User-Agent: weather-app/1.0
  • Base URL: https://api.weather.gov
  • Timeout: 30 seconds
  • Authentication: None required (public API)

Troubleshooting

Common Issues

  1. Server won't start: Check that uv is installed and the path in your MCP config is correct
  2. No weather data: Ensure you have internet connectivity and the weather.gov API is accessible
  3. MCP client can't connect: Verify the stdio connection and server logs

Debugging Steps

# Check if uv is installed uv --version # Test the server directly cd ~/weather-mcp uv run python weather.py # Check recent logs tail -20 weather_mcp.log # Test with verbose logging export MCP_LOG_LEVEL=debug uv run python weather.py

Requirements

  • Python 3.11+
  • httpx>=0.28.1
  • mcp[cli]>=1.13.1

Contributing

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature-name
  3. Make your changes and test locally
  4. Check logs for any issues: tail -f weather_mcp.log
  5. Commit and push: git commit -m "Description" && git push
  6. Submit a pull request

API Reference

This server uses the National Weather Service API:

-
security - not tested
F
license - not found
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Enables users to get detailed weather forecasts for any location using coordinates and retrieve active weather alerts for US states. Uses the National Weather Service API with no authentication required.

  1. Quick Start (Mac/Linux)
    1. 1. Clone and Setup
    2. 2. Configure MCP Client
    3. 3. Monitor Server Activity
  2. How It Works
    1. Features
      1. Development Setup
        1. Prerequisites
        2. Local Development
        3. Making Changes
        4. Project Structure
        5. Testing Tools
      2. Configuration Details
        1. Troubleshooting
          1. Common Issues
          2. Debugging Steps
        2. Requirements
          1. Contributing
            1. API Reference

              MCP directory API

              We provide all the information about MCP servers via our MCP API.

              curl -X GET 'https://glama.ai/api/mcp/v1/servers/MinhHieu-Nguyen-dn/weather-mcp-server'

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