The MCP Standard - A Developer's Guide to Building Universal AI Tools with the Model Context Protocol

Master the art of building feature-rich Model Context Protocol (MCP) servers in TypeScript, by designing decoupled, scalable, and future-proof AI systems that are not locked into a single model vendor. In the world of AI development mired in a chaotic mess of proprietary, incompatible APIs, the Model Context Protocol is the open standard that will become the universal language for AI tools. This book will be your invaluable companion for understanding this solution.
The book takes you on a full, hands-on journey through MCP, looking at it not just as a technical specification but also as a way to help AI-native transformation. It first finds the "why , the tool's issue and shows how MCP is the only logical solution. After that, the book goes into deep detail about the protocol's architecture, breaking down the roles of the Host, Client, and Server, and giving you a guide to its main language of Tools, Resources, and Prompts.
Using the official TypeScript SDK, you will learn how to build a full-featured MCP server from scratch. You will learn best practices for everything from schema design with Zod to adding advanced features like elicitation and server-side sampling. The book is unique in its holistic approach. It doesn't just tell you how to do something; it also has a whole section on production readiness and security that talks about the MCP security model, threat landscapes, and client-side hardening.
This book will give developers, architects, and technical leaders not only the tactical skills they need to succeed in the next wave of software development but also the strategic vision they need to do so. By the end of this book, you will not only have learnt how to use the MCP, but you will have gained a deep understanding of MCP in the context of the larger shift from cloud-native to AI-native.
You Will Learn To:

• Master the art of building feature-rich MCP servers in TypeScript, from basic tools to advanced capabilities like elicitation, resource linking, and server-side sampling.
• Understand the complete MCP architecture and protocol specification, enabling you to debug complex interactions and build custom clients or servers.
• Implement a robust, multi-layered security strategy for your MCP deployments, including authentication, authorization, and client-side hardening against common threats.
• Solve the "M x N" integration problem by designing decoupled, scalable, and future-proof AI systems that are not locked into a single model vendor.
• Gain a strategic understanding of MCP's role in the broader AI-native transformation, which empowers you to make informed architectural decisions for your organization.

This Book is For:
Software developers, AI engineers, and solutions architects who are creating apps that interface with large language models should read this book.
 

List of contents

Part I - The Foundation: Why MCP Matters.- Chapter 1 - The Age of Tooling Chaos.- Chapter 2 - The Solution: A Universal Language for AI.- Chapter 3 - MCP and the AI-Native Transformation.- Part II - The Architecture: A Technical Deep Dive.- Chapter 4 - The MCP Architectural Roles.- Chapter 5 - The Language of MCP: Tools, Resources, and Prompts.- Chapter 6 - Under the Hood: The Protocol Specification.- Part III - The Practitioners: Building with MCP.- Chapter 7: For the Tool Provider: Building a Feature-Complete MCP Server.- Chapter 8: For the AI Application Developer: Building a Reactive MCP Client.- Part IV - Security and Production Readiness.- Chapter 9 - The Agentic Threat Landscape.- Chapter 10 - Foundational Security: Authentication.- Chapter 11 - Server-Side Hardening: Mitigating Common Vulnerabilities.- Chapter 12 - LLM-Centric Threats: Injection and Poisoning.- Chapter 13 - Ecosystem and Dynamic Threats.- Part V - The Playbook: A Real-World Case Study.- Chapter 14 - Deep Dive Case Study: Building an Agentic RAG System.- Part VI- The Horizon: The Future of MCP.- Chapter 15 - Navigating the Ecosystem: Servers, Clients, and Registries.- Chapter 16 - The Evolving Ecosystem and What's Next.- Appendix A - MCP Resource Compendium.- Appendix B - Glossary of Terms.

About the author

Srinivasan Sekar
is an AI enthusiast and the Director of Engineering at LambdaTest, where he leads innovation in Agentic AI. His work focuses on building next-generation AI platforms and leveraging the Model Context Protocol (MCP) to create intelligent agentic applications. A passionate advocate for open source, Srinivasan is a recognised Appium member and an active contributor to several prominent projects, including Selenium, Appium, and Webdriver.io. He is a frequent speaker at international technology conferences, providing his deep expertise at events such as SeleniumConf, AppiumConf, and FOSDEM on the architecture and practical application of emerging AI technologies.

Summary

Master the art of building feature-rich Model Context Protocol (MCP) servers in TypeScript, by designing decoupled, scalable, and future-proof AI systems that are not locked into a single model vendor. In the world of AI development mired in a chaotic mess of proprietary, incompatible APIs, the Model Context Protocol is the open standard that will become the universal language for AI tools. This book will be your invaluable companion for understanding this solution.
The book takes you on a full, hands-on journey through MCP, looking at it not just as a technical specification but also as a way to help AI-native transformation. It first finds the "why”, the tool's issue — and shows how MCP is the only logical solution. After that, the book goes into deep detail about the protocol's architecture, breaking down the roles of the Host, Client, and Server, and giving you a guide to its main language of Tools, Resources, and Prompts.
Using the official TypeScript SDK, you will learn how to build a full-featured MCP server from scratch. You will learn best practices for everything from schema design with Zod to adding advanced features like elicitation and server-side sampling. The book is unique in its holistic approach. It doesn't just tell you how to do something; it also has a whole section on production readiness and security that talks about the MCP security model, threat landscapes, and client-side hardening.
This book will give developers, architects, and technical leaders not only the tactical skills they need to succeed in the next wave of software development but also the strategic vision they need to do so. By the end of this book, you will not only have learnt how to use the MCP, but you will have gained a deep understanding of MCP in the context of the larger shift from cloud-native to AI-native.
You Will Learn To:

• Master the art of building feature-rich MCP servers in TypeScript, from basic tools to advanced capabilities like elicitation, resource linking, and server-side sampling.
• Understand the complete MCP architecture and protocol specification, enabling you to debug complex interactions and build custom clients or servers.
• Implement a robust, multi-layered security strategy for your MCP deployments, including authentication, authorization, and client-side hardening against common threats.
• Solve the "M x N" integration problem by designing decoupled, scalable, and future-proof AI systems that are not locked into a single model vendor.
• Gain a strategic understanding of MCP's role in the broader AI-native transformation, which empowers you to make informed architectural decisions for your organization.

This Book is For:
Software developers, AI engineers, and solutions architects who are creating apps that interface with large language models should read this book.
 

Product details

• Authors: Srinivasan Sekar
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Release: 09.06.2026
• EAN: 9798868823633
• ISBN: 9798868823633
• Illustrations: Approx. 300 p.
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Künstliche Intelligenz, Webprogrammierung, Open Source, TypeScript, Web Development, Intelligence Augmentation, Agentic Systems, AI Agents, Model Context Protocol, LLM Tooling, MCP