Hands-On Introduction to Model Context Protocol (MCP)

About this course

This hands-on course provides a practical introduction to the Model Context Protocol (MCP), the open standard that enables AI applications to securely connect to external tools, data sources, and services.

If you've ever wondered how AI assistants can read files, query databases, call APIs, or interact with external systems, this course is for you.

We focus on learning by doing. There are no theory-heavy slides or unnecessary complexity. Instead, you'll build real MCP servers from scratch and connect them to AI clients using the official Python SDK.You'll start by understanding what MCP is, why it was created, and how it standardizes communication between AI models and external capabilities.

Then we'll move straight into practice.

You'll set up your development environment, build your first MCP server with FastMCP, and connect it to real clients for testing and development.

Throughout the course, you'll explore concepts including:

• Model Context Protocol (MCP)MCP servers and clients

FastMCPToolsResourcesPromptsMCP Inspector

Cursor integration

File system serverSQLite database serverREST API integration

Transport protocols

Error handling and logging

Good practices for MCP servers

You'll build practical examples including a sandboxed file system server, a SQLite database server, and an MCP server that exposes external REST API.Although the examples are written in Python, MCP is a language-agnostic protocol with SDKs available for Python, TypeScript, C#, Go, Java, Rust, and other languages. The concepts you'll learn transfer directly regardless of the language you use in production.

Everything is explained through practical examples designed to help you understand not only how MCP works internally, but also how to build reliable integrat

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