MCP Weather Server

A weather application demonstrating the Model Context Protocol (MCP) using FastMCP framework.

What is MCP (Model Context Protocol)?

Model Context Protocol (MCP) is an open standard that enables AI assistants to securely connect to external data sources and tools. Think of it as a universal "plugin system" for AI models that allows them to:

• Access Real-time Data: Connect to databases, APIs, and live systems
• Execute Actions: Perform operations like file management, system commands, or API calls
• Maintain Security: Controlled access with proper authentication and permissions
• Stay Updated: Always work with the latest information rather than static training data

MCP bridges the gap between AI models and the real world by providing a standardized way for models to interact with external systems while maintaining security and reliability.

Key Benefits of MCP:

• Standardized Interface: Consistent protocol across different tools and services
• Security First: Built-in authentication and permission controls
• Real-time Access: Live data instead of stale training information
• Extensible: Easy to add new tools and data sources
• Cross-platform: Works across different AI models and platforms

What is FastMCP?

FastMCP is a Python framework that simplifies building MCP servers. It's designed to make creating MCP-compliant servers as easy as building a REST API with FastAPI.

Key Features:

• Decorator-based: Simple @mcp.tool() decorators to expose functions
• Type Safety: Full TypeScript-like type hints and validation
• Automatic Documentation: Self-documenting APIs with schema generation
• Built-in Server: Ready-to-use server implementation
• Development Tools: Hot reloading and debugging support

Why Use FastMCP vs Core Python MCP SDK?

Feature	FastMCP	Core MCP SDK
Ease of Use	✅ Simple decorators, minimal boilerplate	❌ More verbose, manual setup required
Development Speed	✅ Rapid prototyping and development	⚠️ Slower initial setup
Type Safety	✅ Built-in validation and type checking	⚠️ Manual type validation needed
Documentation	✅ Auto-generated from code	❌ Manual documentation required
Learning Curve	✅ Familiar FastAPI-like syntax	❌ Steeper learning curve
Flexibility	⚠️ Some conventions enforced	✅ Full control over implementation
Performance	✅ Optimized for common use cases	✅ Can be optimized for specific needs

When to Choose FastMCP:

• 🚀 Rapid Development: Need to get a server up quickly
• 🔰 Learning MCP: First time building MCP servers
• 🛠️ Standard Use Cases: Common patterns like API wrappers, data access
• 👥 Team Development: Want consistent, maintainable code

When to Choose Core SDK:

• 🎯 Specific Requirements: Need custom protocol handling
• ⚡ Performance Critical: Require maximum optimization
• 🔧 Advanced Features: Need low-level protocol control
• 🏗️ Custom Architecture: Building complex, multi-component systems

Current Weather API Example

This repository demonstrates a weather MCP server built with FastMCP that provides real-time weather information.

Features

• Weather Lookup: Get current weather for any location
• Location-based: Smart location parsing and validation
• Error Handling: Graceful handling of invalid locations or API failures
• Type Safe: Full type validation for inputs and outputs

Implementation

The weather server exposes a single tool:

@mcp.tool()
def get_weather_info(location: str) -> str:
    """
    Get Weather information for a given location.
    
    Args:
        location (str): The location for which to get the weather information.
                       The location needs to be a proper city name like London, Tokyo etc.
    """

Getting Started

1. Clone the Repository:

   git clone https://github.com/yourusername/MCP_WEATHER.git
   cd MCP_WEATHER
   

2. Create a Virtual Environment:

   uv venv weather_mcp_env
   source weather_mcp_env/bin/activate
   

3. Install Dependencies:

   uv sync or uv pip install -r requirements.txt
   

4. Configuration:

.vscode/mcp.json

{
  "mcpServers": {
    "weather": {
      "command": "path/to/python",
      "args": ["path/to/weather_server.py"]
    }
  }
}

Open the vscode chat agent mode and ask a weather question

what is the weather in Jersey City?

you should see the agent using the MCP server to get the weather information.