MCP-Servers
by junfanz1
This project demonstrates a decoupled real-time agent architecture connecting LangGraph agents to remote tools served by custom MCP (Modular Command Protocol) servers. It enables a flexible and scalable multi-agent system where each tool can be hosted independently, offering modularity and cloud-deployable execution.
Last updated: N/A
What is MCP-Servers?
MCP-Servers is a project focused on implementing and extending an MCP (Model-Controlled Protocol) Server that facilitates real-time, documentation-grounded responses for AI systems. It integrates an MCP client-server architecture enabling AI models to access structured knowledge and invoke specific tools dynamically.
How to use MCP-Servers?
To use MCP-Servers, you can spin up LangChain-compatible MCP tool servers (e.g., math_server.py, weather_server.py) and integrate them with LangGraph ReAct agents. The client libraries (multiserver_client.py, stdio_client.py) provide examples of how to connect agents to these servers using async/await programming for non-blocking I/O.
Key features of MCP-Servers
Decoupled architecture for LLM agent orchestration and tool execution
Real-time, multi-server, and language-agnostic tool integration using MCP
Asynchronous programming for concurrent tool execution and scalable communication
Support for both SSE and STDIO transport protocols
Agentic Composability: multi-layer agentic interactions
Self-Evolving AI via Registry API: dynamic tool discovery
Use cases of MCP-Servers
Building modular and scalable AI applications
Integrating diverse tools and services into LLM workflows
Creating real-time agentic systems with live interaction
Enabling AI models to access structured knowledge and invoke tools dynamically
FAQ from MCP-Servers
What is MCP?
What is MCP?
MCP (Modular Command Protocol) is a protocol for defining and invoking modular tools, enabling seamless transformation and invocation of distributed tools.
What is LangGraph?
What is LangGraph?
LangGraph is a state-machine inspired framework for agentic reasoning.
What are the benefits of using async/await?
What are the benefits of using async/await?
Async/await enables non-blocking I/O, allowing concurrent execution of multiple tools and scalable real-time communication.
What transport protocols are supported?
What transport protocols are supported?
The project supports both SSE (Server-Sent Events) and STDIO (Standard Input/Output) transport protocols.
What is Agent2Agent Protocol?
What is Agent2Agent Protocol?
A2A defines standard way for agents to discover capabilities, agents can advertise their functions, so other agents know what they can do. Agents can assign and track tasks, including complex long running ones, exchanging status updates and results. Agents can securely exchange messages containing context instructions or data.