udayauma/weather-mcp-server

Weather MCP Server

A simple Model Context Protocol (MCP) server that provides weather information and demonstrates the core concepts of building MCP servers.

Features

This MCP server demonstrates:

• Resources: Weather data for different locations (New York, London, Tokyo)
• Tools: Functions to get current weather and forecasts
• Prompts: Templates for weather reports and comparisons

Installation

1. Install the required dependencies:

pip3 install -r requirements.txt

2. (Optional) Create a .env file for configuration:

WEATHER_API_KEY=your_weather_api_key_here
SERVER_NAME=weather-mcp-server
SERVER_VERSION=1.0.0
LOG_LEVEL=INFO

Running the Server

Run the server directly:

python3 weather_mcp_server.py

Available Resources

The server provides weather resources for:

• weather://new_york - Weather for New York, NY
• weather://london - Weather for London, UK
• weather://tokyo - Weather for Tokyo, Japan

Available Tools

1. get_weather: Get current weather for any location

   • Parameters: location (string, required)

2. get_weather_forecast: Get weather forecast for a location

   • Parameters: location (string, required), days (integer, 1-7, default: 3)

Available Prompts

1. weather_report: Generate a detailed weather report

   • Parameters: location (string, required)

2. weather_comparison: Compare weather between two locations

   • Parameters: location1 (string, required), location2 (string, required)

Testing the Server

You can test the server using the MCP inspector tool or integrate it with an MCP-compatible client.

Example Usage

This is a mock implementation that uses sample data. In a real-world scenario, you would:

1. Replace the mock data with actual weather API calls
2. Add authentication and error handling
3. Implement caching for better performance
4. Add more detailed weather information

MCP Protocol Overview

This server implements the Model Context Protocol, which consists of:

• Resources: Static or dynamic data sources that can be read
• Tools: Functions that can be called to perform actions
• Prompts: Template messages for LLM interactions

The server communicates via JSON-RPC over stdio, making it easy to integrate with various MCP clients.

Extending the Server

To add new functionality:

1. Add new tools: Define new functions in the handle_call_tool method
2. Add new resources: Update the handle_list_resources and handle_read_resource methods
3. Add new prompts: Update the handle_list_prompts and handle_get_prompt methods

Dependencies

• mcp>=1.0.0: Model Context Protocol SDK
• httpx>=0.25.0: HTTP client for API calls
• python-dotenv>=1.0.0: Environment variable loading