Most AI agent tutorials stop at a demo. This book takes you all the way to production.
Model Context Protocol (MCP) for AI Developers is a hands-on guide to building real MCP servers and clients-tools, resources, prompts, remote Streamable HTTP services, API and database integrations, and the security controls that keep them safe. You will move from a working server in minutes to deployable systems that hosts like Claude, Cursor, and custom agents can trust.
Inside, you will learn how to design high-quality tools with strict schemas, expose data through resources without leaking the wrong context, wrap REST and GraphQL APIs cleanly, connect databases with least privilege and row-level scoping, and ship remote servers with authentication, rate limits, observability, and CI. Capstone projects pull it together: an internal knowledge-and-database agent, a GitHub and project-management agent, and a full production remote server with auth, data, and third-party APIs.
What sets this book apart is its refusal to stay conceptual. Every chapter prioritizes working patterns, production checklists, and side-by-side Python and TypeScript examples aligned with the modern MCP specification-so you build systems operators can run, not prototypes that collapse under real load.
If you are ready to stop bolting tools onto prompts and start shipping durable agent infrastructure, open Chapter 1 and build your first MCP server today.
