What is Mcp Ag2 Example

mcp-ag2-example is a project that demonstrates the integration of the Model Context Protocol (MCP) with AutoGen (AG2), showcasing a modular approach for building AI agents that utilize various tools and resources.

Use cases

Use cases include building AI assistants that can interact with various tools, automating tasks using LLM capabilities, and developing applications that require seamless integration of multiple AI functionalities.

How to use

To use mcp-ag2-example, clone the repository, install the required dependencies using the uv package manager, and run the example script to see the MCP-enabled agent in action.

Key features

Key features include protocol-level interface abstraction, dynamic tool discovery, model agnosticism, and the ability to utilize MCP resources without needing format conversions for different language models.

Where to use

mcp-ag2-example can be used in fields such as AI development, machine learning, and automation, where modular AI agents can leverage various tools and resources effectively.

MCP-AG2 Integration Example

This project demonstrates the integration of the Model Context Protocol (MCP) with AutoGen (AG2), showcasing a powerful pattern for building modular, tool-enabled AI agents.

Overview

The example implements three key components:

1. MCP Server: A process that exposes resources and tools following the MCP specification
2. MCPAssistantAgent: An AutoGen AssistantAgent extension that implements the MCP client interface
3. Example Script: Demonstrates an MCP-enabled agent using LLM capabilities with MCP resources/tools

Setup

Prerequisites

1. Install uv package manager:

# macOS
brew install uv

# Other platforms
curl -LsSf https://astral.sh/uv/install.sh | sh

Installation

# Clone the repository
git clone https://github.com/jtanningbed/mcp-ag2-example
cd mcp-ag2-example

# Install dependencies
uv sync

# Run the example
uv run example.py

Key Benefits

This integration pattern offers several advantages over traditional tool/function calling implementations:

1. Protocol-Level Interface Abstraction

• The MCP client interface itself (read_resource, call_tool, etc.) is exposed to the LLM agent through AG2’s tool registration
• Rather than registering individual tools directly with AG2, we register only the core MCP interface methods
• All specific tools (e.g., write_file) are proxied through the call_tool interface to the MCP server
• This means tools defined on the MCP server don’t need any format conversion for different LLMs - they remain in Anthropic schema format

2. Dynamic Tool Discovery and Model Agnosticism

• Agents use list_tools to discover available server tools
• While the MCP server defines tools using Anthropic’s schema format, the LLM never sees these directly
• The LLM only needs to understand how to use call_tool with a name and arguments
• No need to convert tool schemas between different LLM formats since they’re abstracted behind the MCP interface

3. Clean Separation of Concerns

• MCP server handles:
  • Tool implementation details
  • Tool schema definitions (in Anthropic format)
  • Resource management
• Agent only handles:
  • Understanding the core MCP interface methods
  • Using call_tool to proxy specific tool requests to the server
• LLM integration layer only handles:
  • Registering MCP interface methods as tools (e.g., call_tool in OpenAI format)
  • Routing tool calls through the MCP client

AutoGen-Specific Benefits

When compared to traditional AutoGen tool implementations:

1. Simplified Tool Integration

   • No need to define tool schemas in multiple formats
   • Tools are defined once on the MCP server in Anthropic format
   • AG2 only needs the call_tool interface registered

2. Enhanced Modularity

   • MCP servers can be used by any MCP-compatible client
   • Tools and resources are completely decoupled from agent implementation
   • New tools can be added to the server without any agent changes

Architecture Overview

graph LR
    A[LLM] -->|Uses| B[AG2 Tool Interface]
    B -->|Registered| C[MCP Interface Methods]
    C -->|Proxy| D[MCP Client]
    D -->|Protocol| E[MCP Server]
    E -->|Implements| F[Tools & Resources]