MCP Engineering Handbook. A software engineer's guide to building production-ready AI integrations with Model Context Protocol

This book is your complete guide to using MCP for building production-ready AI integrations that go far beyond simple chatbots. You’ll also learn how MCP can serve as the backbone of AI software architecture, treating Resources, Prompts, and Elicitation as cohesive building blocks, not isolated features. Starting with the fundamentals, you’ll explore MCP’s architecture and how it solves the M×N integration problem through standardization. You’ll establish connections, work with JSON-RPC, and learn capability negotiation. You’ll also use SDKs in C#, Python, and TypeScript to accelerate development and reduce boilerplate. From there, you’ll dive deep into Tools for model-driven actions, Prompts for messaging and control, Resources for flexible data access, Elicitation for UI input, and Sampling to enable the client to act as an LLM provider. Moving from theory to practice, you’ll build secure MCP servers with proper error handling, logging, and authentication. You’ll implement clients that safely expose capabilities while defending against malicious servers. The book also covers deployment strategies, enterprise patterns, and integration with tools like GitHub Copilot, Claude, and Cursor. By the end, you’ll be ready to design and operate scalable, agentic systems with MCP at their core.