How to Create an MCP Server & LangChain Agent in Python | Full Tutorial |(FastMCP + LangChain)

Description

How to Create an MCP Server & LangChain Agent in Python | Full Tutorial |(FastMCP + LangChain) Learn how to build a fully functional AI Agent in Python using MCP (Model Context Protocol) and LangChain! 🚀 In this hands-on tutorial, we’ll create a simple MCP Server that exposes custom tools — and then connect it to a LangChain Agent powered by Groq’s Llama 3.1 model to execute real tasks (like solving math problems). This video is perfect for beginners and developers who want to understand how MCP servers extend agent capabilities and how to make your AI models use external tools dynamically. 🧩 What You’ll Learn ✅ What is MCP (Model Context Protocol) ✅ How LangChain connects to MCP servers ✅ Setting up a FastMCP server in Python ✅ Defining custom tools (add, multiply) ✅ Connecting MCP with LangChain using MultiServerMCPClient ✅ Using Groq’s Llama 3.1 model with LangChain Agent ✅ Testing the agent to perform real computations 📂 Code Files mcp_server.py → defines the math tools agent.py → connects LangChain to the MCP server All code explained line by line with concept visualization and live demo output! 🔗 Resources 🧠 LangChain docs: https://python.langchain.com ⚙️ MCP reference: https://modelcontextprotocol.io ⚡ Groq API: https://groq.com #LangChain #MCP #PythonAI #AIagent #Groq #Llama3 #FastMCP #CodingTutorial #AITools #LangChainTutorial