agent MCP Client

Use This MCP client To

Connect AI agents to a global multi-agent collaboration network Enable real-time communication between heterogeneous AI agents Coordinate tasks across multiple AI agents seamlessly Integrate existing AI agents into MACNet with minimal code Facilitate multi-agent workflows across different AI frameworks Manage agent identities and context sharing via MCP Build distributed AI systems with interoperable agents

README

AgentMCP: The Universal System for AI Agent Collaboration

Unleashing a new era of AI collaboration: AgentMCP is the system that makes any AI agent work with every other agent - handling all the networking, communication, and coordination between them. Together with MACNet (The Internet of AI Agents), we're creating a world where AI agents can seamlessly collaborate across any framework, protocol, or location.

✨ The Magic: Transform Your Agent in 30 Seconds

Turn any existing AI agent into a globally connected collaborator with just one line of code.

pip install agent-mcp  # Step 1: Install

from agent_mcp import mcp_agent  # Step 2: Import

@mcp_agent(mcp_id="MyAgent")      # Step 3: Add this one decorator! 🎉
class MyExistingAgent:
    # ... your agent's existing code ...
    def analyze(self, data):
        return "Analysis complete!"

That's it! Your agent is now connected to the Multi-Agent Collaboration Network (MACNet), ready to work with any other agent, regardless of its framework.

➡️ Jump to Quick Demos to see it live! ⬅️

What is AgentMCP?

AgentMCP is the world's first universal system for AI agent collaboration. Just as operating systems and networking protocols enabled the Internet, AgentMCP handles all the complex work needed to make AI agents work together:

Converting agents to speak a common language
Managing network connections and discovery
Coordinating tasks and communication
Ensuring secure and reliable collaboration

With a single decorator, developers can connect their agents to MACNet (our Internet of AI Agents), and AgentMCP takes care of everything else - the networking, translation, coordination, and collaboration. No matter what framework or protocol your agent uses, AgentMCP makes it instantly compatible with our global network of AI agents.

📚 Examples

🚀 Quick Demos: See AgentMCP in Action!

These examples show the core power of AgentMCP. See how easy it is to connect agents and get them collaborating!

1. Simple Multi-Agent Chat (Group Chat)

agent-mcp FAQ

How do I integrate AgentMCP with my existing AI agent?

Simply install the package and add the @mcp_agent decorator to your agent class to connect it to MACNet.

Does AgentMCP support agents built on different AI frameworks?

Yes, AgentMCP enables collaboration across any framework or protocol by standardizing communication via MCP.

What networking capabilities does AgentMCP provide?

It handles all networking, communication, and coordination between AI agents in the MACNet ecosystem.

Can I customize the agent identity in AgentMCP?

Yes, you can specify a unique mcp_id when decorating your agent to identify it within the network.

Is AgentMCP compatible with multiple LLM providers?

AgentMCP works agnostically with various LLM providers including OpenAI, Anthropic Claude, and Google Gemini by focusing on protocol-level interoperability.

How does AgentMCP improve multi-agent workflows?

By enabling seamless, real-time collaboration and context sharing between agents, it simplifies complex distributed AI tasks.

What programming languages are supported by AgentMCP?

Currently, AgentMCP is designed for Python agents but can be extended to other languages supporting MCP.

Is there a performance impact when using AgentMCP?

AgentMCP is lightweight and optimized to minimize overhead while enabling robust multi-agent communication.