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Mcp Server

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rrezartprebreza
mcp-server

Use when exposing Spring Boot 3 application capabilities through Model Context Protocol tools, resources, or prompts. Covers Spring AI 1.x tool callback registration, transports, schemas, errors, security, and standalone MCP Java SDK compatibility.

Overview

Publisherrrezartprebreza
Repositoryspring-boot-skills
Skill namemcp-server
Stars
322
Forks
52
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by rrezartprebreza on GitHub. Read the source before you install it.

Installation

Install the Mcp Server AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/rrezartprebreza/spring-boot-skills/tree/main/skills/spring-boot-3/mcp-server
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rrezartprebreza/spring-boot-skills.git /tmp/spring-boot-skills
mkdir -p .claude/skills
cp -r /tmp/spring-boot-skills/skills/spring-boot-3/mcp-server .claude/skills/mcp-server
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mcp Server in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mcp Server on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mcp Server is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MCP Server - Spring Boot 3

Prefer the Spring AI MCP server starters in a Spring Boot application. Let the Spring AI BOM manage its MCP SDK dependency; do not force the standalone SDK version into a starter-based application.

Dependencies

xml
<!-- Pick exactly one transport starter. -->
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-starter-mcp-server</artifactId>
</dependency>
<!-- Remote MVC: spring-ai-starter-mcp-server-webmvc -->
<!-- Remote reactive: spring-ai-starter-mcp-server-webflux -->

For a raw SDK application without Spring AI, use the current MCP Java SDK 2.x release and follow its migration guide. Do not assume raw SDK examples match the version managed by Spring AI 1.x.

xml
<dependency>
    <groupId>io.modelcontextprotocol.sdk</groupId>
    <artifactId>mcp</artifactId>
    <version>2.0.0</version>
</dependency>

Spring AI 1.x tool callback integration

Spring AI 1.0.x exposes @Tool methods only through an explicit MethodToolCallbackProvider — a bare @Component with @Tool methods registers nothing. Spring AI 1.1.x additionally supports native @McpTool/@McpToolParam with spring.ai.mcp.server.annotation-scanner.enabled=true, imported from org.springaicommunity.mcp.annotation (Spring AI 2.0 moved them to org.springframework.ai.mcp.annotation). Pick one registration path per tool.

java
@Configuration
class McpToolsConfiguration {
    @Bean
    ToolCallbackProvider orderTools(OrderMcpTools tools) {
        return MethodToolCallbackProvider.builder()
            .toolObjects(tools)
            .build();
    }
}

@Component
final class OrderMcpTools {
    private final OrderService orderService;

    OrderMcpTools(OrderService orderService) {
        this.orderService = orderService;
    }

    @Tool(description = "Get an order by UUID with line items and status history")
    OrderResponse getOrder(
            @ToolParam(description = "Order UUID") String orderId) {
        return OrderResponse.from(orderService.findById(UUID.fromString(orderId)));
    }
}
  • Return DTOs rather than serialized JPA entities.
  • Register each tool object once; duplicate providers create duplicate capabilities.
  • Keep tool names and descriptions stable because clients and models depend on them.
  • Bound result size, execution time, and downstream calls.
  • For raw SDK code, use builders such as CallToolResult.builder(); old constructors were removed.

Transport configuration

yaml
spring:
  main:
    banner-mode: "off"
  ai:
    mcp:
      server:
        name: order-service-mcp
        version: 1.0.0
        type: SYNC
        stdio: true

Use stdio when a local client launches the jar. Use the matching MVC or WebFlux starter and Streamable HTTP for a remote server when supported by the selected Spring AI 1.x release. Keep stdout clean in stdio mode because it carries JSON-RPC frames.

Security and verification

  • Authenticate and authorize remote MCP endpoints and every underlying domain operation.
  • Validate identifiers, enum values, pagination, and result limits.
  • Do not expose secrets, stack traces, persistence entities, or unrestricted administrative tools.
  • Test discovery, invalid arguments, authorization, timeouts, and shutdown with a real MCP client.
  • Review the selected Spring AI 1.x release notes before copying 2.0 annotation examples.

Examples

  • See examples/OrderMcpTools.java, examples/good-order-tools.java, and examples/bad-order-tools.java.

Official sources

Gotchas

  • Agent overrides the MCP SDK under Spring AI 1.x - let the Spring AI BOM manage it.
  • Agent copies Spring AI 2.0 org.springframework.ai.mcp.annotation imports into a 1.1 project - 1.1 uses org.springaicommunity.mcp.annotation, and 1.0 has no MCP annotations at all.
  • Agent expects @Tool methods on a plain @Component to appear as MCP tools in 1.x - register them through a ToolCallbackProvider bean.
  • Agent passes --spring.ai.mcp.server.transport=stdio - no such property; Boot ignores it silently. Use spring.ai.mcp.server.stdio=true.
  • Agent uses removed new CallToolResult(...) constructors in raw SDK code - use builders.
  • Agent logs to stdout in stdio mode - route logs to stderr or a file and disable the banner.
  • Agent registers the same tool object twice - keep one callback provider per capability.
  • Agent exposes entities or unbounded collections - return bounded DTO contracts.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mcp Server AI skill do?

Use when exposing Spring Boot 3 application capabilities through Model Context Protocol tools, resources, or prompts. Covers Spring AI 1.x tool callback registration, transports, schemas, errors, security, and standalone MCP Java SDK compatibility.

Why use Mcp Server on TypingMind?

Because you install it once and use it with any model. Mcp Server is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mcp Server in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rrezartprebreza/spring-boot-skills/tree/main/skills/spring-boot-3/mcp-server. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mcp Server?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mcp Server?

As many as you like. As long as a model supports skills, you can use Mcp Server with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mcp Server AI skill free?

Yes. It is published on GitHub by rrezartprebreza under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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