The Model Context Protocol is no longer experimental. With tens of millions of monthly SDK downloads and native support from OpenAI, Google, Microsoft, and Anthropic, MCP is now the default standard for connecting AI agents to the real world. But the gap between building a toy weather server and operating a PCI-DSS-compliant enterprise gateway remains vast and largely undocumented.
This book closes that gap.
MCP: The Missing Manual for AI Agents is the most comprehensive guide to MCP architecture, security, and production operations available today. Across six parts and 22 chapters, you will learn how to design MCP servers that survive real traffic, harden them against prompt injection and tool poisoning attacks, scale them to thousands of users, and navigate the full 2026 protocol stack including A2A, ACP, and UCP.
The interview preparation section alone is worth the price. Featuring 50+ real questions modeled on interviews at top AI companies, 10 company-specific playbooks, and the Gotcha Index - the wrong answers that kill candidacies every day - this is the book candidates wish they had before walking into their toughest technical interview.
Three production case studies show exactly what breaks and why: a schema drift incident, a data exfiltration event, and a $2.3 million inventory oversell caused by two agents sharing a database connection pool. Theory is nice. Production is what ships.
Whether you are building, securing, scaling, or interviewing, this is the manual that should have shipped with the protocol.