icon for mcp server

AutoGen

STDIO

Enhanced AutoGen MCP server for sophisticated multi-agent conversations with workflow support.

AutoGen MCP Server

smithery badge

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
  1. Install dependencies:
pip install -e .

Configuration

Environment Variables

  1. Copy .env.example to .env:
cp .env.example .env
  1. 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
  1. 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" }
  1. Execution Errors
{ "error": "Agent not found" }
  1. 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

Be the First to Experience MCP Now