MCP ChatBot

🚀 MCP-ChatBot

A versatile chatbot application that uses the Modular Capability Protocol (MCP) to interact with multiple service backends.

🚀 Quick Start

MCP-ChatBot is a containerized application that demonstrates how to use the Modular Capability Protocol (MCP) to enable Large Language Models (LLMs) to interact with external services. This implementation includes a weather service backend and a Streamlit-based front-end interface, allowing users to query weather information through natural language.

✨ Features

• Containerized Architecture: The MCP server and client applications run in separate containers.
• Weather Service Integration: Uses WeatherAPI to obtain real-time weather data.
• Streamlit UI: A clean and responsive interface for interacting with the chatbot.
• Scalable Design: More MCP servers can be added at any time to implement more functions.
• GPT-4o Integration: Powered by OpenAI's GPT-4o model for natural language understanding.

🔧 Technical Details

The application consists of two main components:

1. MCP Server: A FastMCP-based service responsible for retrieving weather data.
2. Streamlit Client: A web interface for interacting with the chatbot.

📦 Installation

Prerequisites

• Docker and Docker Compose
• WeatherAPI key (register at WeatherAPI)
• OpenAI API key (register at OpenAI)

Steps

1. Clone the repository:

   git clone https://github.com/yourusername/MCP-ChatBot.git
   

2. Copy the example environment file:

   cp .env.example .env
   

3. Start the Docker service:

   docker-compose up --build
   

📚 Documentation

Extending the Application

• Add a New Server: Create a new file in the servers folder and write the configuration in the format of the existing servers.
• Update the Configuration: Edit the docker-compose.yml file to add a new service definition.

Development Information

• Project Structure:

  • src/: Contains the core source code.
  • templates/: Contains HTML templates and UI components.
  • static/: Contains static resource files.

• Technology Stack:

  • FastMCP: For MCP protocol implementation.
  • Streamlit: For front-end interface development.
  • WeatherAPI: For weather data acquisition.

Troubleshooting

• Common Issues:
  • Ensure that Docker and Docker Compose are installed correctly.
  • Check the configuration in the .env file.
  • If you cannot connect to the weather service, check if the API key is valid.

📄 License

The project details the terms of use of the MIT license in the LICENSE file.

Acknowledgments

• FastMCP: Provides the MCP server implementation.
• Streamlit: Provides the front-end framework.
• WeatherAPI: Provides weather data.

Created by Murali Anand © 2025