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Udemy

The Complete Model Context Protocol (MCP) Masterclass

via Udemy

Overview

Master MCP (Model Context Protocol) - Build Universal AI Agent Integrations from Scratch to Production

What you'll learn:
  • Build and deploy functional MCP servers using multiple transport protocols including STDIO, SSE, and Streamable HTTP
  • Implement MCP tools, resources, and prompts to create intelligent AI agent integrations with external systems and databases
  • Develop a complete end-to-end MCP server application with recipe management, search functionality, and meal planning capabilities
  • Test, debug, and deploy MCP servers to production environments while integrating them with popular AI platforms like Claude Desktop

Unlock the power of seamless AI integrations with the Model Context Protocol (MCP) in this comprehensive, hands-on course designed for developers and AI enthusiasts!

You'll dive deep into MCP, the universal adapter that's revolutionizing how AI applications communicate with external systems. Whether you're building LLM-powered tools or AI agents, MCP provides the standardized bridge between your AI and the world of APIs, databases, and services.

You'll start by exploring what MCP is and why it's essential for modern AI applications. Then we'll examine server-client architecture, dive into the three core MCP transports (STDIO, SSE, and Streamable HTTP), and understand how MCP solves critical integration challenges for LLMs and AI agents.

What You'll Learn:

  • MCP Fundamentals: Master the architecture, core concepts, and communication lifecycle of MCP servers and clients

  • Transport Protocols: Deep dive into STDIO, SSE, and Streamable HTTP transports with their pros and cons

  • Hands-on Development: Build multiple MCP servers from simple chat tools to complex SQL-powered systems

  • MCP Resources & Prompts: Implement advanced features like dynamic resources and intelligent prompting

  • Real-World Projects: Create a complete Recipe MCP Server with tools, resources, and prompts

  • Production Deployment: Deploy your MCP servers remotely and integrate them with VS Code, Claude Desktop, and other AI platforms

  • Testing & Debugging: Use MCP Inspector and other tools to thoroughly test your implementations

Who This Course is For:

  • Developers building AI agents and LLM applications

  • Software engineers wanting to integrate AI with existing systems

  • AI enthusiasts interested in cutting-edge integration protocols

  • Beginners with basic programming knowledge who want to build production-ready AI integrations

Hands-on Projects Include:

  • Community chat MCP server

  • SQLite-powered country data server

  • Complete recipe management system with search, storage, and meal planning

  • Remote deployment on Render with live testing

By the end of this course, you'll be able to build, test, and deploy MCP servers that seamlessly connect AI agents to any external system or API. You'll understand how to create the universal adapters that make AI applications truly powerful and connected.

Whether you're building chatbots, AI assistants, or complex agent systems, this course will equip you with the skills to create robust, scalable AI integrations using the industry's emerging standard.

This course is eligible for the Codestars Certificate Authority (CCA) certificate. Students can take the official exam via codestarscom, and those who pass the quiz will receive their CCA certificate. (more details in the course!)

Join now and master the protocol that's shaping the future of AI integrations!

Syllabus

  • Introduction
  • MCP Quick Overview
  • MCP Deep Dive - Main Concepts
  • Download Code and Resources
  • MCP Hands-on - Build Simple MCPs and Testing
  • MCP Hands-on: MCP Resources and Prompts
  • MCP Hands-on: Build an End-to-End - E2E - MCP Server
  • MCP Hands-on: Deploying an MCP Server on a Remotely
  • Wrap up

Taught by

Codestars • over 2.5 million students worldwide! and Paulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor

Reviews

4.5 rating at Udemy based on 210 ratings

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