3 pages from the guide: the cover, the contents (60 questions in 9 sections) and one complete question with its answer, code and interview tips.
MCP lets AI applications use tools and data from external servers through one protocol, and Java teams now have the MCP Java SDK and the Spring AI starters to build both sides. This guide answers 60 practical questions in nine sections: what MCP is and is not, transports and protocol versions, building servers with @McpTool, @McpResource and @McpPrompt, building clients and using tools through ChatClient, configuring Claude Code and Claude Desktop, authorization and security, tool design and testing, limits and mistakes, and a cheat sheet. It is dated October 2026 and follows spec revision 2026-07-28, and it says where the Java SDK and Spring AI releases documented at the time still target earlier revisions.
60 questions in 9 sections, 59 code examples in a 77-page PDF (2026 edition).
100 copy-paste AI prompts for debugging, DevOps, DSA, system design, APIs, microservices and career, in 10 PDFs.
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Work through the sections in order the first time: concepts, transports, then the server and client chapters. Build the small server from the sample question, connect it to the MCP Inspector and to Claude Code or Claude Desktop, and keep the cheat sheet section open as a reference. The code is illustrative and was not compiled or executed for this edition, so compile it against the library versions you use.
Use Spring Boot 4.1.x with the Spring AI 2.0.2 BOM and spring-ai-starter-mcp-server-webmvc, set spring.ai.mcp.server.protocol=STREAMABLE, and write one @SpringBootApplication class plus one @Component with two @McpTool methods. The starter finds the annotated methods and serves them on POST /mcp.
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It covers this topic in depth. It is one topic from the TechTribers Java Interview Series, which has all 23 parts (1,200+ questions) in one bundle.
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60 practical Claude Code answers: CLAUDE.md, context, plan mode and permissions, skills, subagents, hooks, MCP, git and GitHub Actions, cost and security limits, plus a cheat sheet. Checked Oct 2026.
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A self-paced data engineering program from foundations to job-ready skills: SQL, Python, ETL, Airflow and projects.
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