tradmangh/at-xpo-windy-mcpserver

🌤️ Windy MCP Server

Connect AI assistants to real-time weather data from Windy.com

Overview

The Windy MCP Server is a Model Context Protocol (MCP) server that bridges AI assistants with the comprehensive weather data from Windy.com. MCP is an open protocol that enables seamless integration between AI applications (like Claude Desktop) and external data sources.

This server empowers AI assistants to:

• Fetch detailed weather forecasts for any location worldwide
• Discover nearby webcams for visual weather verification
• Generate shareable Windy.com map links with customized layers

Use Cases:

• Claude Desktop: Enhance conversations with real-time weather insights
• AI Automation: Build weather-aware workflows and decision systems
• Chatbots: Integrate live weather data into customer support or travel bots
• Personal Assistants: Create weather-informed task planning and recommendations

Features

🎯 get_point_forecast

Get detailed weather forecasts for any coordinates with precision and flexibility.

Capabilities:

• Temperature: Current and forecasted temperature data
• Wind: Speed, direction, and gusts - perfect for sailors, pilots, and outdoor enthusiasts
• Precipitation: Rain, snow, and precipitation probability
• Pressure: Atmospheric pressure readings for weather pattern analysis
• Multiple Forecast Models: Choose from GFS, ECMWF, ICON-EU, and more for different accuracy levels and update frequencies

📷 get_webcams

Discover webcams near any location for visual weather verification and real-time conditions.

Capabilities:

• Location-Based Search: Find webcams within a specified radius
• Visual Verification: Perfect for confirming actual weather conditions
• Webcam Metadata: Access webcam details, titles, and locations
• Image URLs: Direct links to current webcam images

🗺️ get_map_link

Generate shareable Windy.com map URLs with customizable views.

Capabilities:

• Customizable Layers: Wind, rain, temperature, clouds, waves, and more
• Zoom Configuration: Set the perfect zoom level (1-19) for your needs
• Center Point: Focus the map on any coordinates
• Instant Sharing: Create links to share weather visualizations with others

Quick Start

Follow these steps to get the Windy MCP Server up and running:

# Clone the repository
git clone https://github.com/tradmangh/at-xpo-windy-mcpserver.git
cd at-xpo-windy-mcpserver

# Install dependencies
npm install

# Set up your API key
cp .env.example .env
# Edit .env and add your WINDY_API_KEY

# Build the server
npm run build

# Start the server
npm start

Configuration

Environment Variables

Getting a Windy API Key

1. Visit https://api.windy.com/
2. Create an account or sign in
3. Navigate to the API keys section
4. Generate a new API key for your application
5. Copy the key and add it to your .env file

Integration Examples

Claude Desktop Configuration

To use this MCP server with Claude Desktop, add the following configuration to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "windy": {
      "command": "node",
      "args": ["/absolute/path/to/at-xpo-windy-mcpserver/build/index.js"],
      "env": {
        "WINDY_API_KEY": "your-api-key-here"
      }
    }
  }
}

Replace /absolute/path/to/at-xpo-windy-mcpserver with the actual path where you cloned the repository, and your-api-key-here with your actual Windy.com API key.

Example Prompts for AI Assistants

Once configured, you can use natural language prompts like:

• "What's the wind forecast for Lake Neusiedl tomorrow?"
• "Find webcams near Podersdorf, Austria"
• "Show me the temperature forecast for Tarifa, Spain for the next 3 days"
• "Generate a Windy map link for kitesurfing conditions in Tarifa with wind overlay"
• "What's the weather like at coordinates 47.8095, 16.7644?"
• "Are there any webcams near the Golden Gate Bridge?"

API Reference

get_point_forecast

Retrieve weather forecast data for specific coordinates.

Input Parameters:

Example Request:

{
  "lat": 47.8095,
  "lon": 16.7644,
  "model": "gfs",
  "parameters": ["temp", "wind", "rain"],
  "levels": ["surface"]
}

Example Response:

{
  "lat": 47.8095,
  "lon": 16.7644,
  "model": "gfs",
  "parameters": {
    "temp": [15, 16, 17, ...],
    "wind": [5.2, 6.1, 7.3, ...],
    "rain": [0, 0, 0.5, ...]
  },
  "ts": [1234567890, 1234571490, ...]
}

get_webcams

Find webcams near a specific location.

Input Parameters:

Example Request:

{
  "lat": 47.8095,
  "lon": 16.7644,
  "radius": 50
}

Example Response:

{
  "result": {
    "total": 5,
    "webcams": [
      {
        "id": "1234567890",
        "title": "Podersdorf Beach",
        "location": {
          "latitude": 47.8123,
          "longitude": 16.7701
        },
        "image": {
          "current": "https://..."
        }
      }
    ]
  }
}

get_map_link

Generate a shareable Windy.com map URL.

Input Parameters:

Example Request:

{
  "lat": 47.8095,
  "lon": 16.7644,
  "zoom": 12,
  "layer": "wind"
}

Example Response:

Windy Map URL: https://www.windy.com/?wind,47.8095,16.7644,12

Development

Prerequisites

• Node.js: Version 18 or higher
• npm: Comes with Node.js
• Windy.com API Key: Required for accessing weather data

Development Setup

# Install dependencies
npm install

# Run in development mode (with ts-node)
npm run dev

# Build TypeScript to JavaScript
npm run build

# Run the built server
npm start

# Run tests (when available)
npm test

Project Structure

at-xpo-windy-mcpserver/
├── src/
│   ├── index.ts          # Main server entry point
│   ├── tools.ts          # Tool definitions and handlers
│   └── *.test.ts         # Test files
├── build/                # Compiled JavaScript output
├── .env.example          # Environment variable template
├── package.json          # Node.js dependencies and scripts
├── tsconfig.json         # TypeScript configuration
└── README.md             # This file

Related Projects

🌐 windy.at - A companion web portal that provides weather forecasts tailored for windsurfers, kiters, sailors, and outdoor enthusiasts. Visit windy.at to explore weather conditions, forecasts, and spot information for locations worldwide. Perfect for planning your next adventure on the water or in the mountains!

Contributing

We welcome contributions! Whether it's bug reports, feature requests, documentation improvements, or code contributions, your input is valuable.

How to Contribute

1. Report Issues: Use the GitHub Issues page to report bugs or request features
2. Submit Pull Requests: Fork the repository, make your changes, and submit a PR
3. Improve Documentation: Help us make the docs better by submitting corrections or additions
4. Share Feedback: Let us know how you're using the Windy MCP Server

For detailed contribution guidelines, see .

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0).

This means:

• ✅ You can use this software for any purpose
• ✅ You can modify the software
• ✅ You can distribute the software
• ✅ You can use the software privately
• ⚠️ If you run a modified version on a server, you must make the source code available to users

See for the full license text.

Acknowledgments

• Windy.com - For providing the excellent weather API and visualization platform
• Anthropic - For developing the Model Context Protocol specification and Claude
• MCP Community - For building an ecosystem of tools and integrations

Questions or Need Help? Open an issue on GitHub or check out the Windy API documentation.