Building an AI-Powered MCP Server with Spring AI: Querying Produ…

What is Building an AI-Powered MCP Server with Spring AI: Querying Product Data without APIs?

This MCP server is built with Spring AI and Spring Boot to expose a Product table (with fields like name, code, quantity, and price) to AI assistants using the Model Context Protocol. It eliminates the need for custom REST APIs by enabling context-aware querying of product data through an AI chat client.

How to use Building an AI-Powered MCP Server with Spring AI: Querying Product Data without APIs?

Set up the server using Spring Initializr with the dependencies spring-boot-starter-data-jpa, spring-ai-starter-mcp-server-webflux, and postgresql. The corresponding client requires spring-ai-starter-mcp-client-webflux, spring-ai-starter-model-ollama, and spring-boot-starter-web. After configuration, an AI chat client can query the product data directly via the MCP protocol.

Key features of Building an AI-Powered MCP Server with Spring AI: Querying Product Data without APIs

• Exposes product data without custom API endpoints.
• Leverages Spring AI’s MCP support for AI agent interaction.
• Uses JPA and PostgreSQL for product storage.
• Integrates with an Ollama‑based AI chat client.
• Enables intuitive, context‑aware queries from AI assistants.

Use cases of Building an AI-Powered MCP Server with Spring AI: Querying Product Data without APIs

• Querying product details (name, code, quantity, price) via a chat interface.
• Allowing AI assistants to retrieve product inventory data without building a separate API.
• Demonstrating how to combine Spring AI, MCP, and a relational database for backend exposure.