What are the runtime dependencies?
Python and the `agent-mcp` package. The decorator requires no additional infrastructure setup.
@geniusgeek
基本信息
MCPAgent for Grupa.AI Multi-agent Collaboration Network (MACNET) with Model Context Protocol (MCP) capabilities baked in
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"agent-mcp": {
"command": "python",
"args": [
"demos/network/test_deployed_network.py"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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.
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.
Python and the `agent-mcp` package. The decorator requires no additional infrastructure setup.
AgentMCP connects to a hosted network at `https://mcp-server-ixlfhxquwq-ew.a.run.app`. Authentication and messaging are managed automatically.
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.
The `@mcp_agent` decorator automatically registers the agent, obtains an access token, and maintains the connection. No manual authentication steps are required.
It is built on FastAPI, providing an asynchronous and scalable architecture for agent communication.
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