Raffay0177/MCP-server-using-FAST-MCP

Weather Info App with MCP Server

A simple weather information application built with FastAPI and integrated with an MCP (Model Context Protocol) server for use with Gemini CLI.

📋 Requirements Checklist

• ✅ FastAPI weather application
• ✅ MCP Server implementation
• ✅ Gemini CLI integration
• ✅ MCP tools demonstration
• ✅ Screen recording (see SCREEN_RECORDING_GUIDE.md)

🎥 Screen Recording

IMPORTANT: This repository includes a screen recording demonstrating:

1. MCP server running
2. gemini mcp list command showing available tools
3. Usage of all MCP tools (get_weather, get_weather_batch, check_api_health)

See SCREEN_RECORDING_GUIDE.md for detailed recording instructions.

Project Structure

.
├── weather_api.py      # FastAPI weather application
├── mcp_server.py       # MCP server exposing weather tools
├── requirements.txt    # Python dependencies
├── mcp_config.json    # Gemini CLI MCP configuration
├── demo.py            # Demo script for testing
└── README.md          # This file

Features

• FastAPI Weather API: RESTful API providing weather information
• MCP Server: Exposes weather functionality as MCP tools
• Gemini CLI Integration: Ready to use with Google's Gemini CLI
• Multiple Tools: Get weather for single/multiple cities, health check

Installation

1. Clone this repository:

git clone <your-repo-url>
cd "MCp derver using FAST MCP"

2. Install dependencies:

pip install -r requirements.txt

Running the Application

Step 1: Start the FastAPI Weather Server

In one terminal:

python weather_api.py

The API will be available at http://localhost:8000

You can test it:

# Using curl
curl http://localhost:8000/weather?city=London

# Or using the browser
http://localhost:8000/weather?city=Paris

Step 2: Configure Gemini CLI for MCP

The MCP server uses stdio transport. Create or update your Gemini CLI configuration file:

On Windows: %APPDATA%\Google\Gemini CLI\mcp_config.json

On macOS/Linux: ~/.config/google-gemini-cli/mcp_config.json

Example configuration:

{
  "mcpServers": {
    "weather-info": {
      "command": "python",
      "args": ["<absolute-path-to-mcp_server.py>"],
      "env": {}
    }
  }
}

For Windows, use full path like:

{
  "mcpServers": {
    "weather-info": {
      "command": "python",
      "args": ["B:\\MCp derver using FAST MCP\\mcp_server.py"],
      "env": {}
    }
  }
}

Step 3: Use with Gemini CLI

1. Start Gemini CLI
2. List available MCP tools:

gemini mcp list

3. Use the tools:

# Get weather for a city
gemini mcp call weather-info get_weather --city "Tokyo"

# Get weather for multiple cities
gemini mcp call weather-info get_weather_batch --cities "London,Paris,New York"

# Check API health
gemini mcp call weather-info check_api_health

Available MCP Tools

1. get_weather

Get current weather information for a single city.

Parameters:

• city (required): Name of the city
• country (optional): Country name

Example:

gemini mcp call weather-info get_weather --city "London" --country "UK"

2. get_weather_batch

Get weather information for multiple cities at once.

Parameters:

• cities (required): Comma-separated list of cities

Example:

gemini mcp call weather-info get_weather_batch --cities "Tokyo,Seoul,Beijing"

3. check_api_health

Check if the weather API is running and healthy.

Example:

gemini mcp call weather-info check_api_health

Testing

Run the demo script to test the setup:

python demo.py

API Endpoints

The FastAPI server provides:

• GET / - API information
• GET /health - Health check
• GET /weather?city=<name>&country=<name> - Get weather (GET)
• POST /weather - Get weather (POST with JSON body)

Screen Recording Instructions

To create a screen recording demonstrating the MCP server:

1. Start the FastAPI server: python weather_api.py
2. Open Gemini CLI
3. Show gemini mcp list command to see available tools
4. Demonstrate each tool:
   • get_weather for a single city
   • get_weather_batch for multiple cities
   • check_api_health
5. Show the responses and how they work together

Project Files

• weather_api.py - FastAPI weather application
• mcp_server.py - MCP server exposing weather tools
• demo.py - Testing and demonstration script
• get_path.py - Helper to get correct paths for configuration
• test_mcp_structure.py - Verify MCP imports and structure
• requirements.txt - Python dependencies
• mcp_config.json - Example Gemini CLI configuration

Documentation

• README.md - This file (main documentation)
• QUICK_START.md - Quick setup guide
• setup_instructions.md - Detailed setup instructions
• SCREEN_RECORDING_GUIDE.md - Guide for creating demo video
• PROJECT_SUMMARY.md - Complete project overview

Notes

• The weather data is mock/simulated for demonstration purposes
• Make sure the FastAPI server is running before using MCP tools
• The MCP server communicates with the FastAPI server via HTTP
• All paths in the configuration must be absolute paths

Troubleshooting

MCP server not connecting:

• Ensure FastAPI server is running on port 8000
• Check that the path to mcp_server.py in the config is correct and absolute
• Verify Python is in your PATH

Tools not appearing:

• Restart Gemini CLI after updating the configuration
• Check the MCP server logs for errors
• Verify the configuration JSON syntax is correct