AutoGen MCP Server
Servidor MCP de AutoGen
Un servidor MCP que se integra con el framework AutoGen de Microsoft, lo que permite conversaciones multiagente mediante una interfaz estandarizada. Este servidor permite crear y gestionar agentes de IA que pueden colaborar y resolver problemas mediante interacciones de lenguaje natural.
Características
Cree y administre agentes de AutoGen con configuraciones personalizables
Ejecutar conversaciones individuales entre agentes
Orqueste chats grupales con múltiples agentes
Configuraciones LLM configurables y entornos de ejecución de código
Soporte para agentes proxy tanto de asistente como de usuario
Manejo de errores integrado y validación de respuestas
Related MCP server: Stellastra MCP Server
Instalación
Clonar el repositorio:
git clone https://github.com/yourusername/autogen-mcp.git
cd autogen-mcpInstalar dependencias:
pip install -e .Configuración
Variables de entorno
Copiar
.env.examplea.env:
cp .env.example .envConfigurar las variables de entorno:
# 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-keyConfiguración del servidor
Copiar
config.json.exampleaconfig.json:
cp config.json.example config.jsonConfigurar los ajustes del servidor:
{
"llm_config": {
"config_list": [
{
"model": "gpt-4",
"api_key": "your-openai-api-key"
}
],
"temperature": 0
},
"code_execution_config": {
"work_dir": "workspace",
"use_docker": false
}
}Operaciones disponibles
El servidor admite tres operaciones principales:
1. Creación de agentes
{
"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. Chat individual
{
"name": "execute_chat",
"arguments": {
"initiator": "agent1",
"responder": "agent2",
"message": "Let's discuss the system architecture."
}
}3. Chat grupal
{
"name": "execute_group_chat",
"arguments": {
"agents": ["agent1", "agent2", "agent3"],
"message": "Let's review the proposed solution."
}
}Manejo de errores
Los escenarios de error más comunes incluyen:
Errores de creación de agentes
{
"error": "Agent already exists"
}Errores de ejecución
{
"error": "Agent not found"
}Errores de configuración
{
"error": "AUTOGEN_MCP_CONFIG environment variable not set"
}Arquitectura
El servidor sigue una arquitectura modular:
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 managementLicencia
Licencia MIT: consulte el archivo de LICENCIA para obtener más detalles
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