AgentMCP: Multi-Agent Collaboration Platform

@geniusgeek

About AgentMCP: Multi-Agent Collaboration Platform

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

#mcp #agents #aiagent #aiagents #mcp-servers #mcp-server #mcp-client #awesome-mcp-servers #mcp-server-store #mcp-agent-framework

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"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

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.

FAQ from AgentMCP: Multi-Agent Collaboration Platform

What are the runtime dependencies?

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

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.

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.

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.

What transport does AgentMCP use?

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

Frequently asked questions

What are the runtime dependencies?

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

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.

Which agent frameworks are supported?

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.

What transport does AgentMCP use?

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

Comments

Basic information

More AI & Agents MCP servers

MCP Claude Code

SDGLBL

MCP implementation of Claude Code capabilities and more

302

Solon Ai

opensolon

Java AI application development framework (supports LLM-tool,skill; RAG; MCP; Agent-ReAct,Team-Agent). Compatible with java8 ~ java25. It can also be embedded in SpringBoot, jFinal, Vert.x, Quarkus, and other frameworks.

416