ai.smithery/DynamicEndpoints-autogen_mcp

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# Enhanced AutoGen MCP Server

[![smithery badge](https://smithery.ai/badge/@DynamicEndpoints/autogen_mcp)](https://smithery.ai/server/@DynamicEndpoints/autogen_mcp)

A comprehensive MCP server that provides deep integration with Microsoft's AutoGen framework v0.9+, featuring the latest capabilities including prompts, resources, advanced workflows, and enhanced agent types. This server enables sophisticated multi-agent conversations through a standardized Model Context Protocol interface.

## 🚀 Latest Features (v0.2.0)

### ✨ **Enhanced MCP Support**
- **Prompts**: Pre-built templates for common workflows (code review, research, creative writing)
- **Resources**: Real-time access to agent status, chat history, and configurations
- **Dynamic Content**: Template-based prompts with arguments and embedded resources
- **Latest MCP SDK**: Version 1.12.3 with full feature support

### 🤖 **Advanced Agent Types**
- **Assistant Agents**: Enhanced with latest LLM capabilities
- **Conversable Agents**: Flexible conversation patterns
- **Teachable Agents**: Learning and memory persistence
- **Retrievable Agents**: Knowledge base integration
- **Multimodal Agents**: Image and document processing (when available)

### 🔄 **Sophisticated Workflows**
- **Code Generation**: Architect → Developer → Reviewer → Executor pipeline
- **Research Analysis**: Researcher → Analyst → Critic → Synthesizer workflow
- **Creative Writing**: Multi-stage creative collaboration
- **Problem Solving**: Structured approach to complex problems
- **Code Review**: Security → Performance → Style review teams
- **Custom Workflows**: Build your own agent collaboration patterns

### 🎯 **Enhanced Chat Capabilities**
- **Smart Speaker Selection**: Auto, manual, random, round-robin modes
- **Nested Conversations**: Hierarchical agent interactions
- **Swarm Intelligence**: Coordinated multi-agent problem solving
- **Memory Management**: Persistent agent knowledge and preferences
- **Quality Checks**: Built-in validation and improvement loops

## 🛠️ Available Tools

### Core Agent Management
- `create_agent` - Create agents with advanced configurations
- `create_workflow` - Build complete multi-agent workflows
- `get_agent_status` - Detailed agent metrics and health monitoring

### Conversation Execution
- `execute_chat` - Enhanced two-agent conversations
- `execute_group_chat` - Multi-agent group discussions
- `execute_nested_chat` - Hierarchical conversation structures
- `execute_swarm` - Swarm-based collaborative problem solving

### Workflow Orchestration
- `execute_workflow` - Run predefined workflow templates
- `manage_agent_memory` - Handle agent learning and persistence
- `configure_teachability` - Enable/configure agent learning capabilities

## 📝 Available Prompts

### `autogen-workflow`
Create sophisticated multi-agent workflows with customizable parameters:
- **Arguments**: `task_description`, `agent_count`, `workflow_type`
- **Use case**: Rapid workflow prototyping and deployment

### `code-review`
Set up collaborative code review with specialized agents:
- **Arguments**: `code`, `language`, `focus_areas`
- **Use case**: Comprehensive code quality assessment

### `research-analysis`
Deploy research teams for in-depth topic analysis:
- **Arguments**: `topic`, `depth`
- **Use case**: Academic research, market analysis, technical investigation

## 📊 Available Resources

### `autogen://agents/list`
Live list of active agents with status and capabilities

### `autogen://workflows/templates`
Available workflow templates and configurations

### `autogen://chat/history`
Recent conversation history and interaction logs

### `autogen://config/current`
Current server configuration and settings

## Installation

### Installing via Smithery

To install AutoGen Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@DynamicEndpoints/autogen_mcp):

```bash
npx -y @smithery/cli install @DynamicEndpoints/autogen_mcp --client claude
```

### Manual Installation

1. **Clone the repository:**
```bash
git clone https://github.com/yourusername/autogen-mcp.git
cd autogen-mcp
```

2. **Install Node.js dependencies:**
```bash
npm install
```

3. **Install Python dependencies:**
```bash
pip install -r requirements.txt --user
```

4. **Build the TypeScript project:**
```bash
npm run build
```

5. **Set up configuration:**
```bash
cp .env.example .env
cp config.json.example config.json
# Edit .env and config.json with your settings
```

## Configuration

### Environment Variables

Create a `.env` file from the template:

```bash
# Required
OPENAI_API_KEY=your-openai-api-key-here

# Optional - Path to configuration file
AUTOGEN_MCP_CONFIG=config.json

# Enhanced Features
ENABLE_PROMPTS=true
ENABLE_RESOURCES=true
ENABLE_WORKFLOWS=true
ENABLE_TEACHABILITY=true

# Performance Settings
MAX_CHAT_TURNS=10
DEFAULT_OUTPUT_FORMAT=json
```

### Configuration File

Update `config.json` with your preferences:

```json
{
  "llm_config": {
    "config_li