Cars MCP Server

Cars MCP Server Overview

The Cars MCP Server is a lightweight Spring Boot application that exposes a curated list of cars as AI‑ready tools via the Model Context Protocol (MCP). By leveraging Spring AI’s API, it turns ordinary service methods into callable actions that an AI assistant—such as Claude or other MCP‑compatible agents—can invoke in real time. This enables developers to embed a dynamic, knowledge‑rich resource into their conversational workflows without writing custom integrations.

At its core, the server hosts a small in‑memory catalog of vehicles. The class initializes this list during startup and offers three primary operations:

• Retrieve all cars ()
• Find a car by model name ()
• Search for a car by build year ()

Each method is annotated with , automatically registering it as a . The MCP server then advertises these tools to any connected AI client, allowing the assistant to answer questions like “Show me my wishlist” or “Which car was built in 2025?” with concrete, typed responses. Because the data is local and immutable for the life of the process, latency remains minimal and reliability high.

For developers building AI‑enhanced applications, this server offers several practical advantages. First, it demonstrates a clean separation of concerns: the business logic lives in , while MCP plumbing is handled by Spring Boot and the ToolCallback API. Second, it shows how to expose domain knowledge as tools rather than raw data endpoints—an approach that keeps the assistant’s reasoning surface small and well‑typed. Third, the example can be extended to any domain: replace the car list with products, documents, or inventory items and re‑use the same registration pattern.

Typical use cases include:

• Personal assistant apps that need to recall a user’s vehicle preferences or schedule maintenance reminders.
• E‑commerce chatbots that can pull product details from a catalog when the user asks for specifics.
• Knowledge‑base assistants that expose internal datasets (e.g., HR policies, compliance documents) as callable tools for quick lookup.

Because the server runs without a web layer (), it can be deployed as a lightweight background service or bundled within larger AI platforms. Its configuration is straightforward, relying only on standard Spring properties to name the MCP server and set its version. This simplicity makes it an ideal starting point for teams experimenting with MCP‑driven toolchains or looking to integrate structured data into conversational agents.