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AutoGen MCP Server

by DynamicEndpoints
GitHub
Python
MIT License
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Integrations

  • Supports environment variable configuration through .env files for managing API keys and server settings

  • Provides optional Docker-based code execution environment for the agents when executing code as part of conversations

  • Supports installation via git clone from a repository

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

  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

This server cannot be installed

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An MCP server that provides integration with Microsoft's AutoGen framework, enabling multi-agent conversations through a standardized interface.

  1. Features
    1. Installation
      1. Configuration
        1. Environment Variables
        2. Server Configuration
      2. Available Operations
        1. 1. Creating Agents
        2. 2. One-on-One Chat
        3. 3. Group Chat
      3. Error Handling
        1. Architecture
          1. License

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