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

This book is 75% completeLast updated on 2026-06-02

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

  1. Introduction to the Model Context Protocol (MCP)ch01_introduction_to_mcp.md
  2. Implementing MCP: Transport Mechanismsch02_transport_mechanisms.md
  3. The MCP Communication Flowch03_communication_flow.md
  4. MCP Primitives: Resources, Tools, Prompts and Notificationsch04_primitives.md
  5. The Core Messaging: JSON-RPC 2.0ch05_json_rpc_2_0.md
  6. MCP Protocol Versions & Evolutionch06_mcp_version_history.md
  7. Tool Execution: The tools/call Methodch07_tool_execution.md
  8. Resource Managementch08_resource_management.md

Part II — Building MCP Servers

  1. Implementing a Weather API example app using SSE/httpch09_weather_api_sse.md
  2. Connecting to AI Services (Claude, ChatGPT, Gemini, Cursor)ch10_connecting_to_ai_services.md 10b. Implementing MCP Servers with the JDK Native SDKch10_jdk_native_support.md (currently orphaned — needs sequential number in final re-numbering pass)
  3. Implementing a Local Notes Searcher example app MCP using STDIOch11_local_notes_searcher_stdio.md
  4. Frameworks: The Spring AI MCP Startersch12_spring_ai_framework.md
  5. Implementing MCP Server Using Promptsch13_mcp_prompts_deep_dive.md
  6. Implementing MCP Server Using Resourcesch14_mcp_resources_deep_dive.md
  7. Testing MCP Serversch15_testing_mcp_servers.md

Part III — Advanced Implementation & Clients

  1. Building an MCP Clientch16_building_mcp_clients.md
  2. Implementing MCP from Scratch in Pure Javach17_implementing_from_scratch.md
  3. Sampling and Elicitationch18_sampling_and_elicitation.md
  4. Progress and Long-Running Tasksch19_progress_and_long_running_tasks.md
    • 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 29b. Writing a Well-Behaved Hostch17b_writing_a_well_behaved_host.md (internally numbered 29; file is in Part III directory; conflicts with ch29_non_determinism.md — needs resolution in final re-numbering pass)
  5. The Adapter Pattern: Wrapping Legacy APIsch44_adapter_pattern.md
  6. Stateful Tools and Session Managementch45_stateful_tools.md
  7. Integrating MCP directly with Web Frontendsch46_web_frontends.md
  8. Mocking and Simulating MCP Serversch47_mocking_mcp.md

Part IV — Production & Architecture

  1. Security Fundamentalsch20_security_fundamentals.md
  2. Authentication and Authorization in Depthch21_auth_in_depth.md
  3. Tool Design Principlesch22_tool_design_principles.md
  4. Observability, Metrics, and Debuggingch23_observability_and_metrics.md
  5. Performance, Concurrency, and Scalingch24_performance_and_scaling.md
  6. Kubernetes Deploymentch25_kubernetes_deployment.md
  7. Edge Deploymentch26_edge_deployment.md
  8. Schema Evolution and Migration Strategych27_schema_evolution.md
  9. Cost and Quota Engineeringch28_cost_engineering.md
  10. Non-Determinism and Defensive Designch29_non_determinism.md
  11. Security Deep Dive: Prompt Injection & Tool Poisoningch40_security_prompt_injection.md
  12. Performance Benchmarking & Optimizationch42_performance_benchmarking.md
  13. Building a custom MCP Gatewaych43_mcp_gateway_pattern.md
  14. Data Privacy, PII Redaction, and Compliancech48_data_privacy_pii.md
  15. Deploying MCP to Serverlessch49_serverless_deployment.md

Part V — Agentic Systems & Ecosystem

  1. Agentic Workflows and Tool Compositionch30_agentic_workflows.md
  2. MCP and Retrieval-Augmented Generation (RAG)ch31_mcp_and_rag.md
  3. Multi-Agent Architecturesch32_multi_agent_systems.md
  4. MCP in Automation and CI/CDch33_automation_and_cicd.md
  5. MCP Outside Spring (Plain JDK, Quarkus, Micronaut)ch34_mcp_outside_spring.md
  6. LangChain4j and MCPch35_langchain4j_and_mcp.md
  7. The Capstone Project: Team Assistantch36_capstone_project.md
  8. MCP for Databases & SQLch39_mcp_for_databases_sql.md
  9. The "Personal OS" Assistantch41_personal_os_assistant.md
  10. Polyglot Architectures: Java Servers, Python Clientsch50_polyglot_architectures.md

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