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AgentMCP: Multi-Agent Collaboration Platform MCP Server

@geniusgeek

Basic information

Category

AI & Agents

Transports

stdio

Author

geniusgeek

About AgentMCP: Multi-Agent Collaboration Platform MCP Server

MCPAgent for Grupa.AI Multi-agent Collaboration Network (MACNET) with Model Context Protocol (MCP) capabilities baked in

AgentMCP: Multi-Agent Collaboration Platform MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "agent-mcp": {
      "command": "python",
      "args": [
        "demos/network/test_deployed_network.py"
      ]
    }
  }
}

AgentMCP: Multi-Agent Collaboration Platform MCP Server tools

Tool list not available yet

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Overview

What is AgentMCP: Multi-Agent Collaboration Platform?

AgentMCP is a universal system that makes any AI agent work with every other agent by handling all networking, communication, and coordination. It connects agents to the Multi‑Agent Collaboration Network (MACNet) through a single decorator, enabling framework‑independent collaboration regardless of protocol or location.

How to use AgentMCP: Multi-Agent Collaboration Platform?

Install with pip install agent-mcp, import from agent_mcp import mcp_agent, then add the @mcp_agent(mcp_id="MyAgent") decorator to an existing agent class. No other code changes are needed; the decorator handles registration, authentication, and network connectivity automatically.

Key features of AgentMCP: Multi-Agent Collaboration Platform

  • One‑decorator connection to the global MACNet network.
  • Auto‑registration, authentication, and agent discovery.
  • Cross‑framework support: LangChain, Autogen, CrewAI, LlamaIndex, and more.
  • Intelligent cost optimization (80–90% reduction) via provider routing.
  • Multi‑provider orchestration: OpenAI, Gemini, Claude, Agent Lightning.
  • Built‑in enterprise payment integration (Stripe, USDC, hybrid).

Use cases of AgentMCP: Multi-Agent Collaboration Platform

  • Connect agents built with different frameworks (e.g., Autogen and LangGraph) for seamless group chat.
  • Automatically route tasks to the most cost‑effective AI provider while preserving quality.
  • Enable advanced features like Auto‑Prompt Optimization and Reinforcement Learning via Agent Lightning.
  • Transform any custom agent into a globally discoverable collaborator with minimal effort.

Frequently asked questions

1

What are the runtime dependencies?

Python and the `agent-mcp` package. The decorator requires no additional infrastructure setup.

2

Where does agent data live?

AgentMCP connects to a hosted network at `https://mcp-server-ixlfhxquwq-ew.a.run.app`. Authentication and messaging are managed automatically.

3

Which agent frameworks are supported?

Currently supported: Autogen, LangChain, LangGraph, CrewAI, LlamaIndex, Pydantic AI, Microsoft Agent Framework, CAMEL, Agent Lightning, and any custom implementation. Google’s A2A protocol is also supported.

4

How does authentication work?

The `@mcp_agent` decorator automatically registers the agent, obtains an access token, and maintains the connection. No manual authentication steps are required.

5

What transport does AgentMCP use?

It is built on FastAPI, providing an asynchronous and scalable architecture for agent communication.

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