Weather Chat Assistant 🌤️

A modern weather chat interface built with Streamlit and powered by the Model Context Protocol (MCP). Get real-time weather information and forecasts for any location worldwide through a friendly chat interface.

Features

• 🌍 Global Weather Data: Get weather for any city worldwide
• ☀️ Current Weather: Real-time temperature, conditions, humidity, and wind data
• 📅 Weather Forecasts: Up to 3-day weather predictions
• 💬 Chat Interface: Natural language queries like "What's the weather in London?"
• 🎨 Modern UI: Beautiful, responsive Streamlit interface
• 🔧 MCP Integration: Built using Model Context Protocol architecture

Quick Start

Option 1: Direct Streamlit Deployment

1. Clone or download this repository

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the Streamlit app:

   streamlit run streamlit_app.py
   

4. Open your browser to the URL shown (usually http://localhost:8501)

Option 2: Deploy to Streamlit Cloud

1. Fork this repository to your GitHub account

2. Go to Streamlit Cloud

3. Deploy by connecting your GitHub repository

4. Set the main file as streamlit_app.py

The app will automatically deploy and be available at your Streamlit Cloud URL!

MCP Server (Advanced Usage)

For developers interested in the MCP server component:

Setup MCP Server

1. Navigate to the MCP server directory:

   cd weather-mcp-server
   

2. Install MCP dependencies:

   pip install -r requirements.txt
   

3. Run the MCP server:

   python weather_mcp_server.py
   

4. Test the server (in another terminal):

   python -c "
   import asyncio
   from mcp_client import WeatherMCPClient
   
   async def test():
       client = WeatherMCPClient()
       if await client.connect():
           result = await client.get_weather('London')
           print(result)
           await client.disconnect()
   
   asyncio.run(test())
   "
   

Usage Examples

Once the app is running, try these example queries:

• Current Weather:

  • "What's the weather in London?"
  • "Temperature in Tokyo"
  • "Weather for New York"

• Weather Forecasts:

  • "Show me the forecast for Paris"
  • "3-day forecast for Sydney"
  • "Weather forecast for Berlin for 2 days"

API & Data Source

• Weather Data: Powered by wttr.in - a free weather service
• No API Key Required: Uses a public weather service
• Global Coverage: Weather data for cities worldwide
• Real-time Updates: Current conditions and forecasts

Architecture

graph TD
    A[User Input] --> B[Streamlit App]
    B --> C[Message Parser]
    C --> D[Weather API Client]
    D --> E[wttr.in API]
    E --> F[Weather Data]
    F --> G[Formatted Response]
    G --> H[Chat Interface]
    
    I[MCP Server] --> J[Weather Tools]
    J --> K[get_weather]
    J --> L[get_forecast]

Components

1. Streamlit App (streamlit_app.py): Main chat interface
2. MCP Server (weather-mcp-server/weather_mcp_server.py): Weather tools server
3. MCP Client (weather-mcp-server/mcp_client.py): Client for MCP communication
4. Weather API: Direct integration with wttr.in weather service

File Structure

weather-chat-assistant/
├── streamlit_app.py           # Main Streamlit application
├── requirements.txt           # Streamlit dependencies
├── README.md                 # This file
└── weather-mcp-server/       # MCP server components
    ├── weather_mcp_server.py # MCP server with weather tools
    ├── mcp_client.py         # MCP client for communication
    └── requirements.txt      # MCP server dependencies

Deployment Options

1. Streamlit Cloud (Recommended)

• ✅ Free hosting
• ✅ Automatic deployment from GitHub
• ✅ Custom domain support
• ✅ Easy updates via Git push

2. Local Development

• ✅ Full control
• ✅ Instant feedback
• ✅ Easy debugging

3. Other Platforms

• Heroku: Add Procfile with web: streamlit run streamlit_app.py --server.port=$PORT
• Railway: Direct deployment from GitHub
• Render: Automatic builds from repository

Troubleshooting

Common Issues

1. "Module not found" errors:

   pip install -r requirements.txt
   

2. Network timeouts:

   • Check internet connection
   • Try different location names
   • Wait a moment and retry

3. Streamlit port conflicts:

   streamlit run streamlit_app.py --server.port 8502
   

Debug Mode

To enable detailed logging, set the environment variable:

export PYTHONPATH=.
python -c "import logging; logging.basicConfig(level=logging.DEBUG)"
streamlit run streamlit_app.py

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

License

This project is open source and available under the MIT License.

Support

• 📧 Issues: Open a GitHub issue for bugs or feature requests
• 💬 Discussions: Use GitHub Discussions for questions
• 📖 Documentation: Check this README and code comments

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Built with ❤️ using Streamlit and MCP

Get weather information the modern way - just ask! 🌤️