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AutoGen MCP Server

by DynamicEndpoints
GitHub
Python
MIT License
1
OverviewInspectNewSchemaRelated ServersReviewsScore
Need Help?View Source CodeReport Issue

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

-
security - not tested
A
license - permissive license
-
quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

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. Creating Agents
        2. One-on-One Chat
        3. Group Chat
      3. Error Handling
        1. Architecture
          1. License

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