
AutoGen MCP Server
An MCP server that provides integration with Microsoft's AutoGen framework, enabling multi-agent conversations through a standardized interface.
README
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
- Clone the repository:
git clone https://github.com/yourusername/autogen-mcp.git
cd autogen-mcp
- Install dependencies:
pip install -e .
Configuration
Environment Variables
- Copy
.env.example
to.env
:
cp .env.example .env
- 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
- Copy
config.json.example
toconfig.json
:
cp config.json.example config.json
- 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:
- Agent Creation Errors
{
"error": "Agent already exists"
}
- Execution Errors
{
"error": "Agent not found"
}
- 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
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