Spring MCP Bridge Overview

Spring MCP Bridge solves a common pain point for developers who want to expose their existing Spring Boot REST APIs to AI assistants without rewriting or re‑architecting the services. By automatically scanning a Spring Boot project, it generates an MCP (Message Conversation Protocol) server that mirrors every controller endpoint as a tool. This allows assistants such as Claude, Cursor, or any MCP‑compatible client to invoke your APIs directly through natural language prompts, turning your back‑end into an AI‑friendly interface.

The bridge performs four key steps: scanning, conversion, generation, and forwarding. It parses Java source files to discover controllers, mappings, parameters, and DTOs, then translates Java types into JSON Schema so that the MCP schema accurately describes request and response shapes. A lightweight FastAPI application is produced, routing incoming MCP calls to the original Spring Boot endpoints. The result is a ready‑to‑run MCP server that requires no changes to the original codebase—developers can simply point the bridge at a project folder and receive a fully documented MCP schema in seconds.

Key capabilities include:

• Zero‑configuration operation: No manual edits to controllers or annotations are necessary; the bridge works out of the box.
• Model preservation: Request and response DTOs are kept intact, ensuring type safety and clear documentation for the AI client.
• Javadoc extraction: Existing JavaDoc comments become descriptive tool summaries, improving the assistant’s ability to explain and use each endpoint.
• Complete documentation: The generated MCP server exposes both the FastAPI OpenAPI docs and a well‑known MCP schema endpoint, making integration straightforward for developers.

Typical use cases involve building conversational interfaces over legacy services. For instance, a support chatbot could query inventory or order status by invoking the MCP tools generated from the same Spring controllers that power a web portal. In research settings, data scientists might use an AI assistant to compose complex API calls without memorizing HTTP details. The bridge also facilitates rapid prototyping of AI‑driven workflows, allowing teams to test new conversational features against production logic without duplicating endpoints.

Because the bridge produces a standard MCP server, it fits seamlessly into existing AI pipelines. Developers can deploy the generated FastAPI app alongside their Spring Boot service, configure an MCP client to point at it, and immediately gain a natural‑language interface. The combination of automatic scanning, schema fidelity, and minimal friction makes Spring MCP Bridge a standout tool for modern AI‑centric development.