Craig Walls: AI Superpowers: Model Context Protocol in Java & Spring AI

**Please take a moment to forward this information to co-workers, friends, and social networks. Be sure to register.** **This meetup is co-scheduled with AI Coding & Cloud, Boulder Java Users Group, and Denver Java Users Group hosted at the dev2next conference at the Denver Marriot South.** 6:30-7:00: Food, Soda, and Networking 7:00-7:15: Announcements & Raffles! **7:15-8:30: AI Superpowers: Model Context Protocol in Java & Spring AI** On their own, Large Language Models (LLMs) are only able to generate responses based on their training. While their training may be vast, it will not include any actual data from your organization's databases and systems. What's more, an LLM may be able to answer questions, they are unable to actually interact with your enterprise and take action. Enter Model Context Protocol (MCP). MCP defines a standard with which you can collection a set of related tools, prompts, and resources and make those available to an LLM to make use of. With MCP, your LLMs will be able to interact with databases, APIs, and other components in your enterprise to get things done. Building and using MCP in Java has never been easier than it is now with Spring AI. Spring AI introduced support for MCP in its 1.0 release and improved upon it tremendously in Spring AI 2.0. In this example-driven session, you'll learn how to build an MCP server in Java using Spring AI, integrate it with clients such as Claude Code and Cursor, and even create your own MCP clients.