Build AI Agents with MCP (Model Context Protocol) The Hands-On Guide to Multi-Server Architecture Using FastMCP and Spring

Code. Architect. Orchestrate. Deploy.

Build AI systems that work in the real world.

Move beyond prompts and prototypes. This book is your blueprint for building real, secure, and scalable AI systems using the Model Context Protocol (MCP) — the open standard that lets any model connect to any data source or tool through a universal interface.

Across five progressive sections and 16 chapters, you’ll go from first principles to a production-ready, multi-programming-language AI network — complete with secure data access, hallucination intercepts, orchestration, and enterprise-grade deployment.

WHAT YOU’LL BUILD

I. FOUNDATION & SETUP

Understand the integration challenge, prepare your zero-cost enterprise workstation, and deploy the protocol inspector dashboard.

II. PROTOTYPE WITH PYTHON

Build your first MCP server, create a secure read-only data library, and connect models to live web data safely.

III. BUILD BACKEND WITH JAVA

Engineer a robust Spring Boot backend with repositories, transactions, and hallucination intercepts.

IV. ORCHESTRATE WITH CLIENT

Create the orchestration layer that manages context, routing, concurrency, and intelligent tool selection.

V. DEPLOY & SCALE

Ditch local pipes. Upgrade your Java vault to SSE web hosting, lock it down with API key interceptors, and rewire your Python client to connect over the open internet.

INSIDE YOU’LL FIND

✔ Real hands-on chapters — every line of code complete and unredacted
✔ Python (FastMCP) + Java (Spring Boot) — full polyglot architecture
✔ JSON-RPC 2.0, stdio pipes, SSE streaming, and capability handshaking
✔ Hallucination intercepts and API key handler interceptors
✔ A multi-server orchestrator that coordinates Java and Python simultaneously
✔ Step-by-step environment setup — Python, JDK 25, VS Code
✔ A repeatable chapter structure: theory➜build➜test➜review

WHO THIS BOOK IS FOR

• Developers ready to move beyond demos
• Engineers building enterprise-grade AI systems
• Architects designing secure, scalable integrations
• Tech leaders driving AI strategy and automation