• Coding
• Tutorials
• AUTHOR: codevision AI engine
• DZone AI/ML

This article explains how to create an MCP server using Spring Boot and Spring AI, allowing integration with large language models (LLMs) and external tools. The guide walks through setting up a server that can access tools like get_artists and search_artist, enabling data retrieval when the LLM cannot answer directly. It also covers the use of DevoxxGenie as a human-in-the-loop interface to approve tool calls. The example demonstrates how to build a flexible backend for LLMs, making it easier to extend to other tools and systems. Gunter Rotsaert provides a clear, step-by-step tutorial that is worth reading for developers interested in AI integration.

Key facts

• The article provides a step-by-step guide to creating an MCP server using Spring Boot and Spring AI.
• The MCP server acts as a bridge between large language models (LLMs) and external tools like databases or APIs.
• Tools such as get_artists and search_artist are implemented to fetch and filter data from predefined lists.
• Devo,xxGenie is used as a human-in-the-loop interface to approve tool calls, ensuring safety and control.
• The approach allows developers to focus on tool logic while building a scalable and flexible backend for LLMs.