Overview

Build real MCP servers - without the confusion. Model Context Protocol (MCP) is quickly becoming a standard way for AI systems to connect with tools, data, and workflows. But most explanations are abstract, fragmented, or overly complex. This book takes a practice-first approach. You will learn MCP through a real Python project: a working MCP server that inspects and removes EXIF metadata from images. Along the way, you will see how MCP works in practice: how clients discover capabilities, how structured calls flow through the system, and how to design servers that are safe, predictable, and useful. What you will learn What MCP is and why it matters How MCP servers communicate using JSON-RPC and transports like stdio and HTTP How to build tools, resources, and prompts with clear, structured contracts How to run and test a local MCP server step by step How to connect your server to clients like VS Code and MCP Inspector How to design safe, production-leaning tools with stable outputs How to extend a real project into your own MCP services Built around a real projectThis book is centered on a practical, open-source MCP server that: Reads and analyzes EXIF metadata from images Detects privacy-sensitive fields such as GPS data Safely removes metadata with clear, predictable behavior Demonstrates batch workflows and structured results Who this book is for Developers and builders exploring MCP AI engineers working with tools and integrations Technical creators who prefer learning by doing Anyone looking for a clear, concrete example of a real MCP server This is not a deep Python tutorial or a computer vision book. It is a focused, hands-on guide to building MCP servers that actually work.

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