For my recent presentation at SnowCamp on AI Standards & Protocols for AI Agents, I decided to build an MCP server to access the arXiv research paper website where pre-print versions are published and shared with the community.

My goal was to shed light on some lesser-known aspects of the Model Context Protocol:

• 🛠️ While the majority of MCP servers use the tools feature to expose actions that LLMs can request to call,
• 📄 An MCP server can also share resources (and resource templates), exposing various static assets the AI app might be interested in,
• ✏️ And prompts (and prompt templates) that users can access and reuse to utilize the MCP server effectively.

Note: For the impatient, feel free to go straight to the GitHub repository for the full source code. The README.md file gives instructions on how to build, run, configure, and use the server.

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As I’m contributing to ADK (Agent Development Kit) for Java, and LangChain4j (the LLM orchestration framework) I interact with MCP (Model Context Protocol) servers and tools to further expand the capabilities of my LLMs.

Recently, I showed how to vibe-code an MCP server using Micronaut. You know I usually talk about Micronaut, but this time, I wanted to experiment with Quarkus, and in particular with its built-in support for implementing MCP servers.

Getting started with Quarkus’ MCP support

I created a brand new Quarkus project from IntelliJ IDEA, with its Quarkus template, and I added a couple key dependencies for JSON marshalling, but even more important, for the MCP support: