Build Powerful AI Agents with MCP + LangGraph: Multi-Server Integration Tutorial

Описание: Learn how to create intelligent AI agents by integrating Model Context Protocol (MCP) with LangGraph! In this comprehensive tutorial, you'll discover how to build a multi-server MCP client that connects to both math and weather services, creating a powerful AI agent system.
🔥 What You'll Learn:

Setting up Multi-Server MCP Client with LangGraph
Creating custom MCP servers for math operations
Building weather services with FastMCP
Implementing stdio and HTTP transport protocols
Creating reactive AI agents with Claude integration
Best practices for MCP server development

⚡ Key Technologies Covered:

LangGraph for AI agent orchestration
Model Context Protocol (MCP) for tool integration
FastMCP for rapid server development
Claude 3.5 Sonnet for intelligent responses
Python async/await patterns

🛠️ Perfect for:

AI developers and engineers
Python developers interested in AI agents
Anyone building intelligent automation systems
Developers working with LangChain ecosystem

📚 Prerequisites:

Basic Python knowledge
Understanding of async programming


Familiarity with AI/ML concepts

🎯 Timestamps:
00:00 - Introduction & Overview
02:30 - MCP Architecture Explained
05:15 - Setting Up Multi-Server Client
08:45 - Building Math MCP Server
12:30 - Creating Weather Service
16:20 - LangGraph Agent Integration
20:10 - Testing & Deployment
23:45 - Best Practices & Tips

Girhub: https://github.com/NajiAboo/MCP_tutor...

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