Model Context Protocol (MCP) is emerging as a core standard for building context-aware, tool-enabled, and production-grade AI systems. This course is a complete, hands-on journey that takes you from MCP fundamentals all the way to Designing, Dockerizing, and deploying real-world MCP systems.
You’ll start by understanding what MCP is, why it exists, and the real problems it solves in modern AI ecosystems. From there, you’ll progressively build MCP servers and clients, explore real MCP ecosystems, implement advanced server capabilities, and finally deploy a production-ready MCP system using Docker.
This course is designed for developers and AI builders who want practical, real-world MCP skills, not just conceptual knowledge.
Course Structure & What You’ll Learn
1. MCP Introduction:
- Introduction to Model Context Protocol (MCP)
- What MCP is and how it works
- Problems MCP solves in the AI ecosystem
- MCP adoption trends and ecosystem overview
- Understanding the complete course structure
2. MCP Architecture & Core Concepts:
- MCP client–server architecture
- MCP primitives and core building blocks
- MCP transport layers: STDIO & Streamable HTTP
- How MCP enables scalable, tool-based AI systems
3. Development Environment Setup & Tooling:
- Setting up the MCP development environment
- MCP client setup using Claude Desktop
- Understanding MCP resources and tooling
4. MCP Quick Start – Building Your First MCP Server:
- Project setup and initialization
- Creating your first MCP server
- Testing and debugging using MCP Inspector
- Integrating your MCP server with an existing MCP client (Claude Desktop)
5. MCP Server Ecosystem:
- Overview of the existing MCP server ecosystem
- Understanding real-world MCP server use cases
- Case Study: Airbnb MCP Server
