What are the runtime requirements for Spring MCP Server?
Java 21, Maven 3.9.9, Spring Boot 3.4.4, Spring AI 0.4.0, and the Spring Model Context Protocol Server dependency are required. The application is built and run as a JAR file.
@deepanshu-rawat6
Basic information
A basic implementation of MCP server using Spring Boot
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Spring MCP Server is a Spring Boot application that implements the Model Context Protocol (MCP) to expose data and tools to AI-powered clients. It is built with Spring AI and Spring Model Context Protocol Server, and is intended for developers who want to create secure, two-way connections between their data sources and AI tools like Claude Desktop.
Create a Spring Boot application with the Spring Model Context Protocol Server dependency, define service classes annotated with @Tool, and register tool callbacks in a @Bean method. Build the application with mvn clean package -DskipTests and configure it in claude_desktop_config.json by specifying the Java command and the path to the generated JAR file. Start Claude Desktop to see the installed MCP server and its available tools.
@Tool annotation to expose Java methods as MCP toolsJava 21, Maven 3.9.9, Spring Boot 3.4.4, Spring AI 0.4.0, and the Spring Model Context Protocol Server dependency are required. The application is built and run as a JAR file.
The server uses the stdio transport protocol. Clients such as Claude Desktop are configured to launch the JAR file as a subprocess and communicate via standard input/output.
Tools are defined by annotating methods in a Spring service class with `@Tool(name = "...", description = "...")`. The annotated methods are then registered as tool callbacks using `ToolCallbacks.from(service)` in a Spring `@Bean` method.
Data is defined in Java code within the service class, typically loaded at startup (e.g., via `@PostConstruct`). The README example stores data in a static list inside the service.
The README only demonstrates integration with Claude Desktop. The configuration uses `claude_desktop_config.json`, but the underlying MCP standard could support other clients that implement the same protocol.

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