Скачать или смотреть How to Use LangGraph Agents as MCP Clients | Full Demo & Architecture Explained

Unlock the power of LangGraph Agents by turning them into MCP (Model Context Protocol) Clients.
In this video, I walk you through how LangGraph can connect with multiple MCP servers, execute tools, manage state, and build powerful agentic workflows for real-world applications.

🔍 What You’ll Learn
What is MCP and why it matters for agentic AI
How LangGraph acts as an MCP client
Connecting multiple MCP servers using MultiServerMCPClient
Building a tool-enabled, stateful LangGraph agent
Real demo with tool execution & workflow explanation
High-level architecture for LangGraph + MCP setup

🛠️ Technologies Covered
LangGraph
MCP Server / MultiServerMCPClient
LangChain OpenAI
Python Async IO
Agentic AI Architecture

📌 Use Cases
Code auditing agents
Data-processing agents
Multi-tool enterprise AI assistants
On-prem agent orchestration
Secure AI workflows with controlled tools

📁 Reference Resources
   • Building an MCP Server with FastMCP: Quick...  

💬 Have Questions?
Drop your doubts in the comments — I reply to everyone.

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