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What you need to know about MCP servers - with Java and spring-boot

Peter Isberg

Model Context Protocol (MCP) servers with Java and Spring Boot allow you to standardize how your applications connect to AI assistants and LLMs by exposing internal data and functions as structured, tool-based endpoints. By leveraging the Spring AI framework, you can easily implement MCP protocols to securely bridge your business logic with intelligent agents. This approach simplifies integration, enabling your services to be dynamically discoverable and actionable within an AI-driven ecosystem.

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About

About

About the Book

The Model Context Protocol (MCP) is barely two years old, but it has already become the way serious AI systems talk to the rest of the world. The specification is compact, the reference SDKs are polished, and every major AI vendor — Anthropic, OpenAI, Google — now speaks it natively. What is still missing, for the Java community in particular, is a practical, honest guide that walks you from the JSON-RPC wire format all the way to a production deployment on Kubernetes.

This book is that guide.

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About the Author

Peter Isberg

Peter Isberg is from Sweden with 16+ years professional experience as a software developer. He is a doer and he has mainly been doing things in industries like defense, automotive, online travel and logistics using Java and its landscape

Contents

Table of Contents

  • Part I — Protocol Fundamentals
    • 1. Introduction to the Model Context Protocol (MCP)
    • 2. Implementing MCP: Transport Mechanisms
    • 3. The MCP Communication Flow
    • 4. MCP Primitives: Resources, Tools, Prompts and Notifications
    • 5. The Core Messaging: JSON-RPC 2.0
    • 6. MCP Protocol Versions & Evolution
    • 7. Tool Execution: The tools/call Method
    • 8. Resource Management
  • Part II — Building MCP Servers
    • 9. Implementing a Weather API example app using SSE/HTTP
    • 10. Connecting to AI Services (Claude, ChatGPT, Gemini, Cursor)
    • 11. Implementing a Local Notes Searcher example app using STDIO
    • 12. Frameworks: The Spring AI MCP Starters
    • 13. Implementing MCP Server Using Prompts
    • 14. Implementing MCP Server Using Resources
    • 15. Testing MCP Servers
  • Part III — Advanced Implementation & Clients
    • 16. Building an MCP Client
    • 17. Implementing MCP from Scratch
    • 18. Sampling and Elicitation
    • 19. Progress and Long-Running Tasks
      • 19.1 The protocol contract
      • 19.2 The Spring AI API
      • 19.3 Indeterminate progress
      • 19.4 Multi-phase tasks
      • 19.5 Throttling strategies
      • 19.6 Progress from background threads
      • 19.7 Cancellation awareness
      • 19.8 Capability and client support
      • 19.9 Testing progress notifications
      • 19.10 Design checklist
    • 44. The Adapter Pattern: Wrapping Legacy APIs
    • 45. Stateful Tools and Session Management
    • 46. Integrating MCP Directly with Web Frontends
    • 47. Mocking and Simulating MCP Servers
  • Part IV — Production & Architecture
    • 20. Security Fundamentals
    • 21. Authentication and Authorization in Depth
    • 22. Tool Design Principles
    • 23. Observability, Metrics, and Debugging
    • 24. Performance, Concurrency, and Scaling
    • 25. Kubernetes Deployment
    • 26. Edge Deployment
    • 27. Schema Evolution and Migration
    • 28. Cost and Quota Engineering
    • 29. Non-Determinism and Defensive Design
    • 40. Security Deep Dive: Prompt Injection & Tool Poisoning
    • 42. Performance Benchmarking & Optimization
    • 43. Building a Custom MCP Gateway
    • 48. Data Privacy, PII Redaction, and Compliance
    • 49. Deploying MCP to Serverless
  • Part V — Agentic Systems & Ecosystem
    • 30. Agentic Workflows and Tool Composition
    • 31. MCP and Retrieval-Augmented Generation (RAG)
    • 32. Multi-Agent Architectures
    • 33. MCP in Automation and CI/CD
    • 34. MCP Outside Spring (Plain JDK, Quarkus, Micronaut)
    • 35. LangChain4j and MCP
    • 36. The Capstone Project: Team Assistant
    • 39. MCP for Databases & SQL
    • 41. The "Personal OS" Assistant
    • 50. Polyglot Architectures: Java Servers, Python Clients
  • Part VI — The Future
    • 37. The MCP Ecosystem
    • 38. The Road Ahead
  • Part VII — The MCP Cookbook
    • 51. MCP for IT Operations (AIOps)
    • 52. MCP for Enterprise Support (Helpdesk)
  • Back Matter
    • About the Author
    • MCP Jargon & Glossary
    • Appendix A: Quick Reference

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