Building MCP Servers

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 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

This 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

• 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.