pip install -e .

cp .env.example .env

# 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

cp config.json.example config.json

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

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

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

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

{
  "error": "Agent already exists"
}

{
  "error": "Agent not found"
}

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

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