Model Context Protocol Servers in Practice: Designing Intelligent -Aware Systems, Tool Integration Layers, and Scalable Modern Interfaces (Modern Agentic AI Systems Series)

Cypher, Camila

ISBN 13: 9798195125790

Published by Independently published, 2026

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Seller Inventory # I-9798195125790

Bibliographic Details

• Title: Model Context Protocol Servers in Practice: Designing Intelligent -Aware Systems, Tool Integration Layers, and Scalable Modern Interfaces (Modern Agentic AI Systems Series)
• Publisher: Independently published
• Publication Date: 2026
• Language: English
• ISBN 13: 9798195125790
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Model Context Protocol Servers in Practice focuses on building the infrastructure that allows AI systems to interact with tools, services, and external environments in a consistent and structured way. As applications become more complex, managing how models access and use context becomes a critical part of system design. This book provides a clear and practical approach to solving that problem.
The Model Context Protocol introduces a standardized way for language models to communicate with external systems. This book explores how to implement servers that act as intermediaries between models and the tools they rely on, enabling more reliable and organized interactions.
Readers will learn how to design systems that expose capabilities to models in a controlled manner, ensuring that tool usage is predictable and secure. The book explains how to structure requests, manage responses, and maintain context across interactions without creating fragile or tightly coupled systems.
Through practical examples, the book demonstrates how to build servers that connect AI applications to APIs, databases, and external services. It also covers how to manage state, handle multiple concurrent interactions, and design systems that can grow alongside evolving application needs.
This book is particularly valuable for developers working on platforms, automation systems, and advanced AI applications where consistency and scalability are essential. It focuses on creating clean interfaces between models and the environments they operate in, making it easier to extend functionality without rewriting core logic.
By working through the concepts and implementations presented, readers will gain the ability to build structured AI systems that are easier to maintain, integrate, and scale. The result is a more reliable foundation for developing modern applications powered by language models.