MCP-Based Weather Information System

A Python-based project that provides weather information using MCP tools and includes a simple web dashboard for viewing weather details. The project integrates WeatherAPI for live weather data and Google Gemini API for AI-powered responses through FastMCP.

Features

• MCP Server

• Retrieves current weather information for any location.

• Generates AI-powered responses using Google Gemini.

• Weather Dashboard

• Provides an interactive and user-friendly interface.

• Displays weather details for the selected city instantly.

Project Structure

MCP/
├── my_mcp_server.py      # MCP and HTTP server
├── weather_dashboard.py  # Weather dashboard UI
├── weather.html          # Legacy static page
├── .env                  # API keys and setup
└── venv/                 # Virtual environment

Requirements

• Python 3.10 or higher

• WeatherAPI API key

• Google Gemini API key

Installation

1. Create a Virtual Environment

python -m venv venv
.\venv\Scripts\Activate.ps1

2. Install Dependencies

pip install mcp python-dotenv requests google-genai

3. Create a .env File

GOOGLE_API_KEY=your_google_api_key
WEATHER_API_KEY=your_weather_api_key
WEATHER_API_BASE_URL=https://api.weatherapi.com/v1
MCP_SERVER_PORT=8001
HTTP_SERVER_PORT=8002
WEATHER_DASHBOARD_PORT=8080

Running the Weather Dashboard

Start the dashboard:

python weather_dashboard.py

Open:

http://localhost:8080

Steps

1. Enter a location (e.g., Delhi).

2. Click the Get Weather button.

3. View weather details instantly.

Running the MCP Server

Start the server:

python my_mcp_server.py

Health Check

curl http://localhost:8002/health

Example Tool Request

curl -X POST http://localhost:8002/ `
-H "Content-Type: application/json" `
-d '{"tool":"get_current_weather","args":{"location":"London"}}'

Available MCP Tools

Notes

• Use accurate city names for better results.

• Keep the .env file secure and private.

Technologies Used

• Python – Core programming language used for developing the application.

• FastMCP – Framework used to create and manage MCP tools and services.

• Requests – Python library used for making HTTP requests to external APIs.

• Python Dotenv – Used to load environment variables from a .env file.

• Google Gemini API – Used to generate AI-powered text responses.

• WeatherAPI – Provides real-time weather data for different locations.

• HTML, CSS, and JavaScript – Used to create an interactive web interface.

Project Results

Image 1: Weather Dashboard Home Interface

Image 2: Real-Time Weather Information Interface