# MCP Server

A Model Context Protocol (MCP) server implementation with LLM integration and chat memory capabilities.

## Features

- **MCP Server**: Full Model Context Protocol server implementation
- **LLM Integration**: Support for OpenAI and Anthropic models
- **Chat Memory**: Persistent conversation storage and retrieval
- **Tool System**: Extensible tool framework for various operations

## Installation

1. Clone this repository:
```bash
git clone <repository-url>
cd MCP
```

2. Install dependencies:
```bash
pip install -r requirements.txt
```

Or using the development environment:
```bash
pip install -e .[dev]
```

## Configuration

Set up your API keys as environment variables:

```bash
export OPENAI_API_KEY="your-openai-api-key"
export ANTHROPIC_API_KEY="your-anthropic-api-key"
```

Or create a `.env` file:
```env
OPENAI_API_KEY=your-openai-api-key
ANTHROPIC_API_KEY=your-anthropic-api-key
```

## Usage

### Running the MCP Server

Start the server using the command line:

```bash
python -m mcp
```

Or run directly:
```bash
python mcp.py
```

### Available Tools

The server provides the following tools:

#### Echo Tool
Simple echo functionality for testing.
```json
{
  "name": "echo",
  "arguments": {
    "text": "Hello, world!"
  }
}
```

#### Chat Memory Tools

**Store Memory**
```json
{
  "name": "store_memory",
  "arguments": {
    "conversation_id": "conv_123",
    "content": "User preferences: dark mode enabled",
    "metadata": {"type": "preference"}
  }
}
```

**Get Memory**
```json
{
  "name": "get_memory",
  "arguments": {
    "conversation_id": "conv_123"
  }
}
```

#### LLM Chat Tool
```json
{
  "name": "llm_chat",
  "arguments": {
    "message": "What is the capital of France?",
    "model": "gpt-3.5-turbo"
  }
}
```

### Supported Models

**OpenAI Models:**
- gpt-3.5-turbo
- gpt-4
- gpt-4-turbo
- gpt-4o

**Anthropic Models:**
- claude-3-haiku-20240307
- claude-3-sonnet-20240229
- claude-3-opus-20240229

## Development

### Running Tests

```bash
pytest
```

### Code Formatting

```bash
black .
isort .
```

### Type Checking

```bash
mypy .
```

## Architecture

### Components

- **mcp.py**: Main MCP server implementation and tool registration
- **llmintegrationsystem.py**: LLM provider integration and chat completions
- **chatmemorysystem.py**: Persistent conversation storage with SQLite

### Database Schema

The chat memory system uses SQLite with two main tables:
- `memories`: Individual conversation messages and metadata
- `conversation_summaries`: Conversation overviews and statistics

## Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Submit a pull request

## License

MIT License - see LICENSE file for details.

## Troubleshooting

### Common Issues

**API Key Errors**
Ensure your API keys are properly set in environment variables.

**Database Permissions**
The server creates a `chat_memory.db` file in the current directory. Ensure write permissions.

**Port Conflicts**
The MCP server uses stdio communication by default. No port configuration needed.

### Logging

Enable debug logging:
```bash
PYTHONPATH=. python -c "import logging; logging.basicConfig(level=logging.DEBUG); import mcp; mcp.main()"
```