Agentmcp: Multi Agent Collaboration Platform
AgentMCP is a universal AI agent collaboration system. Through a simple decorator, any AI agent can be connected to the global collaboration network (MACNet) to achieve automatic communication and task coordination across frameworks and protocols.
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What is the MCP server?
The MCP server is the world's first universal AI agent collaboration system. It allows any AI agent to seamlessly collaborate with other agents through a simple decorator (@mcp_agent). Regardless of the framework used by the agents, MCP can handle network connections, communication, and coordination.How to use the MCP server?
Simply install the MCP library and add the @MCP decorator, and your AI agent can immediately join the MCP network and start collaborating with other agents.Applicable scenarios
The MCP server is suitable for complex tasks that require cross - framework collaboration, such as data analysis, multi - model integration, and distributed computing.Main Features
Cross - framework collaborationSupports multiple AI frameworks (such as LangChain, Autogen, etc.), allowing agents from different frameworks to easily cooperate.
Automatic network registrationAgents only need to add the @MCP decorator to automatically register with the MCP network and obtain access rights.
Intelligent task routingAutomatically discover and assign suitable agents to perform tasks based on task requirements.
Advantages and Limitations
Advantages
Easy to use: Cross - framework collaboration can be achieved with just one line of code.
Framework - independent: Supports multiple mainstream AI frameworks without modifying existing code.
Secure and reliable: Built - in authentication and message encryption functions.
Highly scalable: Supports large - scale deployment and task scheduling.
Limitations
Requires a stable network environment.
Some advanced features may require additional configuration.
May impose a certain burden on low - performance devices.
How to Use
Install the MCP library
Run the following command to install the MCP library: pip install agent - mcp.
Add the @MCP decorator
Add the @MCP decorator to your agent class and specify a unique agent ID.
Start the agent
Start your application, and the agent will automatically connect to the MCP network.
Usage Examples
Simple chat exampleTwo agents from different frameworks have a real - time chat through the MCP server.
Task distribution exampleOne agent distributes tasks to other agents for completion.
Frequently Asked Questions
Which AI frameworks does the MCP server support?
How to ensure the security of communication between agents?
Is additional configuration required to use the MCP server?
Related Resources
Official documentation of the MCP server
Detailed usage guides and technical documentation.
GitHub code repository
Open - source code and example projects.
User community
Participate in discussions and seek help.
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