Weather MCP Server

Weather MCP Server

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

Features

Tools

• get_alerts(state: str): Get active weather alerts for a US state (e.g., "CA", "NY")
• Returns formatted alerts with event type, area, severity, description, and instructions

• get_forecast(latitude: float, longitude: float): Get detailed weather forecast for a specific location
• Returns temperature, wind conditions, and detailed forecast for the next 5 periods

Resources

• echo://{message}: Echo resource that returns a formatted message

Project Structure

.
├── server/
│   ├── weather.py          # Main weather MCP server implementation
│   ├── weather.json        # MCP server configuration file
│   └── client.py           # Client example using MCPAgent with memory
├── mcpserver/
│   ├── server.py           # Alternative server implementation with SSE transport
│   ├── client-sse.py       # SSE transport client example
│   ├── client-stdio.py     # STDIO transport client example
│   ├── Dockerfile          # Docker configuration
│   └── requirements.txt    # Python dependencies
├── main.py                 # Project entry point
├── pyproject.toml          # Project configuration and dependencies
└── README.md               # This file

Prerequisites

• Python 3.13 or higher
• uv package manager

Installation

1. Clone the repository:

git clone <repository-url>
cd MCPCRASHCoursemain

1. Create and activate virtual environment:

uv venv
.venv\Scripts\activate  # Windows
# or
source .venv/bin/activate  # Linux/Mac

1. Install dependencies:

uv sync

Or install specific packages: ``bash uv add "mcp[cli]" uv add httpx uv add langchain-groq uv add mcp-use uv add python-dotenv ``

Usage

Running the Weather Server

Option 1: Using the server in server/weather.py (STDIO transport)

uv run mcp dev server/weather.py

Option 2: Using the server in mcpserver/server.py (SSE transport)

cd mcpserver
uv run server.py

The SSE server will run on http://localhost:8000

Running Client Examples

Using MCPAgent Client (with memory)

# Make sure to set GROQ_API_KEY in your .env file
uv run server/client.py

Using SSE Client

# First, start the SSE server in one terminal
cd mcpserver
uv run server.py

# Then in another terminal, run the client
uv run mcpserver/client-sse.py

Using STDIO Client

uv run mcpserver/client-stdio.py

Installing in Claude Desktop

To install the server in Claude Desktop app: ``bash uv run mcp install server/weather.py ``

You'll need to configure it in Claude Desktop's settings. The configuration file is located at server/weather.json.

VS Code Integration

1. Open the project folder in VS Code
2. Open terminal and run:

uv run server/weather.py

1. Press Ctrl+Shift+I to launch chat in VS Code
2. Login with GitHub and setup MCP configuration in VS Code user settings

Configuration

Environment Variables

Create a .env file in the root directory: ``env GROQ_API_KEY=your_groq_api_key_here ``

MCP Server Configuration

The server configuration is in server/weather.json. Update the path to match your system: ``json { "mcpServers": { "weather": { "command": "uv", "args": [ "run", "--with", "mcp[cli]", "mcp", "run", "path/to/server/weather.py" ] } } } ``

Docker Support

Build and run using Docker: ``bash cd mcpserver docker build -t weather-mcp-server . docker run -p 8000:8000 weather-mcp-server ``

API Information

This server uses the National Weather Service API, which is free and doesn't require an API key. The server includes:

• Proper User-Agent headers as required by NWS
• Error handling for API requests
• Formatted responses for easy reading

Development

Running in Development Mode

For development with MCP Inspector: ``bash uv run mcp dev server/weather.py ``

Testing

Test the server by running the client examples:

• server/client.py - Full-featured client with conversation memory
• mcpserver/client-sse.py - SSE transport example
• mcpserver/client-stdio.py - STDIO transport example

Dependencies

• mcp[cli] - Model Context Protocol framework
• httpx - Async HTTP client for API requests
• langchain-groq - LLM integration (for client examples)
• mcp-use - MCP utilities
• python-dotenv - Environment variable management
• nest-asyncio - Async support for interactive Python

License

See LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues and questions, please open an issue on GitHub.