Generative AI Superpowers

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.

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 1.1.