Recently, I’ve been exploring the Model Context Protocol (MCP) and how to easily create custom servers to extend the capabilities of AI assistants like Gemini CLI which I use daily.

I wanted a way to build these servers in Java without the heavy boilerplate of a traditional Maven or Gradle project, or with a complex framework. The solution? Combining JBang, LangChain4j, and… 🥁… a custom Gemini CLI skill!

In this post, I’ll walk you through how I streamlined the creation of MCP STDIO servers, by creating an agent SKILL.md to replicate what I had learned in my previous article.