saida-d/mcp-findweather

MCP Server for Live Weather

(with CrewAI- Agentic AI Solution)

This project implements an MCP (Model Context Protocol) server to fetch live weather details using the WeatherAPI.com API. It supports querying weather data by city name or latitude/longitude and integrates with CrewAI for agent-based workflows and A2A (Agent-to-Agent) communication for collaborative data processing.

Author by Saida.D

Features

• Real-Time Weather Data: Fetch current weather conditions, including temperature, wind speed, humidity, and more.
• Geolocation Support: Query weather by city name or latitude/longitude coordinates.
• CrewAI Integration: Uses CrewAI agents for data retrieval and summarization.
• A2A Communication: Enables structured agent-to-agent interaction for enhanced data processing.
• FastAPI with SSE: Lightweight MCP server using Server-Sent Events for real-time communication.
• Scalable and Secure: Designed for scalability with robust error handling.

Prerequisites

• Python 3.10 strictly equal or higher version (for crewai_tools)
• A free API key from WeatherAPI.com
• Basic understanding of CrewAI, MCP, and A2A protocols

Installation

1. Clone the Repository:

   git clone https://github.com/your-repo/mcp-findweather.git
   cd mcp-findweather
   

2. Create a Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install Required Packages: Install the necessary Python packages using pip:

   pip install fastapi>=0.100.0 uvicorn>=0.22.0 pydantic>=2.0.0 python-dotenv>=1.0.0 httpx>=0.24.0 mcp>=1.2.1 crewai>=0.118.0 crewai-tools>=0.43.0 crewai-tools[mcp]
   

4. Set Up Environment Variables: Create a .env file in the project root and add your WeatherAPI key:

   WEATHER_API_KEY=your_weatherapi_key_here
   

Project Structure

• mcp_server.py: MCP server implementation using FastAPI to fetch weather data.
• client_crewai.py: CrewAI workflow with agents for fetching and summarizing weather data.
• .env: Environment file for storing the WeatherAPI key.
• README.md: This file.

Usage

1. Start the MCP Server: Run the MCP server to expose the get_weather tool:

   python mcp_server.py
   

   The server will be available at http://localhost:8000/sse.

2. Run the CrewAI Workflow: Execute the CrewAI script to fetch and summarize weather data:

   python client_crewai.py
   

   Example output:

   Weather Report for London: The current temperature is 11°C with a wind speed of 6.1 km/h. The weather is partly cloudy.
   

3. Query Weather Data:

   • By city: The server accepts city names (e.g., "London") and uses WeatherAPI's geolocation to fetch coordinates.
   • By coordinates: Pass latitude and longitude directly (e.g., lat=51.52, lon=-0.11).

Example Code

MCP Server (mcp_server.py)

from fastapi import FastAPI
from mcp.server.fastmcp import FastMCP
import httpx
import json
from typing import Any
from pydantic import BaseModel
import os
from dotenv import load_dotenv

........
........
........

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="127.0.0.1", port=8000)

CrewAI Workflow (client_crewai.py)

from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter

server_params = {
    "url": "http://localhost:8000/sse",
    "transport": "sse"
}
........
........
........
if __name__ == "__main__":
    run_crew()

Configuration

• WeatherAPI Key: Obtain a free API key from WeatherAPI.com and add it to the .env file.
• MCP Server: Runs on localhost:8000 by default. Update the server_params in crewai_weather.py if hosted elsewhere.
• A2A Communication: Implicitly handled via CrewAI task context. Extend with explicit A2A protocols for complex workflows.

Testing

1. Test the MCP Server:

   curl http://localhost:8000/sse
   

2. Test Weather Data: Use a tool like Postman to send a request:

   {
       "city": "London"
   }
   

   Or:

   {
       "lat": 51.52,
       "lon": -0.11
   }
   

Deployment

• Local Development: Run locally for testing.
• Cloud Deployment: Deploy the MCP server on platforms like AWS, Azure, or Heroku for production use.
• Security: Bind the server to 127.0.0.1 for development and validate Origin headers for SSE connections.

Visit MCP Marketplace

search for "findweather" (or) click this link https://mcpmarket.com/server/findweather

Contributing

Contributions are welcome! Please submit a pull request or open an issue for bugs, features, or improvements.

License

MIT License