Overview

Artificial intelligence systems are rapidly evolving from passive response generators into active, tool-using systems capable of interacting with real-world infrastructure. The Model Context Protocol (MCP) represents a major architectural shift in AI system design. Instead of treating AI models as isolated components, MCP enables models to interact with external tools, APIs, file systems, and services through structured, secure communication layers. This book provides a deep, engineering-focused exploration of MCP-based systems, showing how to design and implement AI systems that can execute real tasks, manage workflows, and interact with external environments in a controlled and scalable way. You will move beyond prompt engineering and into AI systems engineering, where models are no longer just generating responses but are actively participating in software execution pipelines. This includes building systems where AI can call tools, retrieve data, manage context, and maintain state across complex workflows. You will learn how to: Design and implement MCP-based AI communication architectures Build structured tool-calling systems for AI models Integrate AI with REST APIs, databases, and external services Manage context, memory, and state across multi-step AI workflows Secure AI execution pipelines against misuse and injection attacks Develop real-world AI applications powered by tool-connected models Handle streaming responses and real-time AI interactions By the end of this book, you will be able to build fully functional AI systems that can interact with external environments, execute tools, and perform real-world actions reliably and securely.

Full Product Details

9798195496234

Table of Contents

Reviews

Author Information

Tab Content 6

Countries Available