Model Context Protocol (MCP) Tutorial: Build a Text-to-SQL MCP Server & AI Agents

AI agents are everywhere, but how do they actually talk to your databases, Notion, or GitHub? Meet the Model Context Protocol (MCP)—the "USB-C for AI" that is revolutionizing how we connect LLMs to external data.

Code Link - https://github.com/sjsoumil/IPL-Text2SQL-MCP

In this MCP server tutorial, we move past the theory and build a real-world mcp server and ai agents project from scratch. We are building a Text-to-SQL MCP server on top of an IPL Cricket Database (2008-2026). You'll learn how to ask questions in natural language and have an AI agent generate, validate, and execute SQL queries automatically.

Chapters-
0:00 - Introduction: The Glue for AI Agents
1:08 - The "N x M" Problem: Why traditional integration fails
2:24 - What is Model Context Protocol (MCP)?
3:08 - Architecture: MCP Host, Client, and Server
4:00 - Understanding Tools, Resources, and Prompts
4:42 - Stdio vs. HTTP Transport Modes
5:00 - MCP vs. Function Calling: What's the difference?
5:37 - Project Overview: IPL Cricket Text-to-SQL (2008-2026)
6:53 - Environment Setup & Dependencies
7:28 - Step 1: Building the Text-to-SQL MCP Server
9:49 - Step 2: Creating the React Agent Client (LangGraph)
10:32 - Defining System Instructions & Agent Logic
12:05 - Live Demo: Running the Server & Querying the DB
13:05 - Why MCP makes AI tools reusable and scalable
14:12 - Wrap Up & Final Recap

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