MCP MultiServer AI Agent System

Example Use Cases

• 1

  Orchestrate LLM workflows with remote tool execution via MCP servers.

• 2

  Real-time, asynchronous communication with multiple tool servers over SSE or STDIO.

• 3

  Interoperable, modular AI capabilities with dynamic tool discovery and agent-to-agent protocols.

Description

This project implements a decoupled, asynchronous MCP server-client system that connects LangGraph agents with remote tools via multiple transport protocols (SSE, STDIO). It supports scalable multi-server connectivity, dynamic tool discovery, and real-time execution, facilitating modular AI workflows and agent-to-agent interoperability. The system is designed for extensibility, cloud deployment, and integration with LLM frameworks like LangChain and LangGraph, enabling advanced AI orchestration and tool invocation.