MCP Simple Chatbot

A simple chatbot implementation using the Model Context Protocol (MCP) to interact with various tools and LLM providers.

Features

• Connect to MCP servers and list available tools
• Execute MCP tools with retry mechanism
• Interact with LLM providers through OpenAI-compatible API
• Manage server connections and resources
• Process user input and LLM responses

Requirements

• Python 3.10+
• uv
• MCP server configuration

Installation

1. Clone the repository:

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

2. Create and activate virtual environment using uv:

uv venv .venv
# On Windows:
.\.venv\Scripts\activate
# On macOS/Linux:
source .venv/bin/activate

3. Install dependencies:

uv pip install -r requirements.txt

4. Copy example configuration files:

cp .env.example .env
cp servers_config.json.example servers_config.json

Configuration

1. Edit .env file with your LLM provider credentials:

For OpenAI:

LLM_API_KEY=your-openai-api-key
LLM_BASE_URL=https://api.openai.com/v1
LLM_MODEL_ID=gpt-4

For Deepseek:

LLM_API_KEY=your-deepseek-api-key
LLM_BASE_URL=https://api.deepseek.com/v1
LLM_MODEL_ID=deepseek-chat

2. Configure MCP servers in servers_config.json:

{
  "mcpServers": {
    "server-name": {
      "command": "npx",
      "args": ""
    }
  }
}

Usage

1. Activate virtual environment:

# On Windows:
.\.venv\Scripts\activate
# On macOS/Linux:
source .venv/bin/activate

2. Run the chatbot:

python main.py

Available commands:

• Type your message to chat
• Type ‘quit’ or ‘exit’ to end the session

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.