AutoGen

AutoGen MCP Server

An MCP server that provides integration with Microsoft's AutoGen framework, enabling multi-agent conversations through a standardized interface. This server allows you to create and manage AI agents that can collaborate and solve problems through natural language interactions.

Features

• Create and manage AutoGen agents with customizable configurations
• Execute one-on-one conversations between agents
• Orchestrate group chats with multiple agents
• Configurable LLM settings and code execution environments
• Support for both assistant and user proxy agents
• Built-in error handling and response validation

Installation

Installing via Smithery

To install AutoGen Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @DynamicEndpoints/autogen_mcp --client claude

Manual Installation

1. Clone the repository:

git clone https://github.com/yourusername/autogen-mcp.git
cd autogen-mcp

2. Install dependencies:

pip install -e .

Configuration

Environment Variables

1. Copy .env.example to .env:

cp .env.example .env

2. Configure the environment variables:

## Path to the configuration file
AUTOGEN_MCP_CONFIG=config.json

## OpenAI API Key (optional, can also be set in config.json)
OPENAI_API_KEY=your-openai-api-key

Server Configuration

1. Copy config.json.example to config.json:

cp config.json.example config.json

2. Configure the server settings:

{
  "llm_config": {
    "config_list": [
      {
        "model": "gpt-4",
        "api_key": "your-openai-api-key"
      }
    ],
    "temperature": 0
  },
  "code_execution_config": {
    "work_dir": "workspace",
    "use_docker": false
  }
}

Available Operations

The server supports three main operations:

1. Creating Agents

{
  "name": "create_agent",
  "arguments": {
    "name": "tech_lead",
    "type": "assistant",
    "system_message": "You are a technical lead with expertise in software architecture and design patterns."
  }
}

2. One-on-One Chat

{
  "name": "execute_chat",
  "arguments": {
    "initiator": "agent1",
    "responder": "agent2",
    "message": "Let's discuss the system architecture."
  }
}

3. Group Chat

{
  "name": "execute_group_chat",
  "arguments": {
    "agents": ["agent1", "agent2", "agent3"],
    "message": "Let's review the proposed solution."
  }
}

Error Handling

Common error scenarios include:

1. Agent Creation Errors

{
  "error": "Agent already exists"
}

2. Execution Errors

{
  "error": "Agent not found"
}

3. Configuration Errors

{
  "error": "AUTOGEN_MCP_CONFIG environment variable not set"
}

Architecture

The server follows a modular architecture:

src/
├── autogen_mcp/
│   ├── __init__.py
│   ├── agents.py      # Agent management and configuration
│   ├── config.py      # Configuration handling and validation
│   ├── server.py      # MCP server implementation
│   └── workflows.py   # Conversation workflow management

License

MIT License - See LICENSE file for details