This tutorial guides developers through creating an MCP client using Spring AI, building on a previously established MCP server. The author, Gunter Rotsaert, explains how to integrate with LMStudio and configure tools for interacting with large language models. Readers will learn to set up a Spring Boot project with specific dependencies and implement a chat interface that leverages MCP servers. The tutorial addresses common pitfalls, such as dependency conflicts, and provides solutions for controlled tool execution. It’s worth reading because it simplifies complex MCP client development, making it accessible for Java developers familiar with Spring Boot.
By following this guide, readers will gain hands-on experience building a functional MCP client that communicates with both local LLMs and external servers.
Key facts
- The tutorial demonstrates creating an MCP client using Spring AI to interact with a previously built MCP server.
- Developers must configure Spring Boot with dependencies for web, MCP client, and LMStudio integration.
- A key challenge involves resolving dependency conflicts to ensure proper LMStudio compatibility.
- The implementation includes a chat controller that uses tools defined in application.properties.
- The tutorial covers advanced topics like controlled tool execution with human-in-the-loop validation.
