Interoperable Agent System
Enables flexible multi-agent systems by connecting LangGraph agents to remote tools served by custom MCP servers.
About
This project demonstrates a decoupled, real-time agent architecture that integrates LangGraph agents with remote tools managed by custom Modular Command Protocol (MCP) servers. It fosters a modular and scalable multi-agent ecosystem where tools can be hosted independently, supporting real-time communication via SSE and STDIO, and facilitating cloud-deployable executions. The system paves the way for an Agent2Agent protocol, where AI agents can share capabilities, coordinate actions, and securely exchange context and data, promising enhanced interoperability and collaboration across diverse applications.
Key Features
- Decoupled architecture for agent orchestration and tool execution
- Supports flexible multi-server connectivity for diverse environments
- Uses async/await for non-blocking I/O and concurrent execution
- Integration of LangGraph with Modular Command Protocol (MCP)
- Implements robust agent-to-tool communication with handshake protocols
- 2 GitHub stars
Use Cases
- Integrating language-agnostic tools using the MCP protocol
- Orchestrating LLM workflows with LangGraph agents
- Building enterprise-grade LLM applications with modular components
Sponsored