spring-ai-mcp-server-patterns

giuseppe-trisciuoglio/developer-kit · updated Apr 8, 2026

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$npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill spring-ai-mcp-server-patterns
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summary

Build MCP servers with Spring AI using declarative tools, prompt templates, and native Spring integration patterns.

  • Exposes Spring components as AI-callable tools via @Tool annotation, with parameter documentation through @ToolParam for AI model understanding
  • Supports three transport modes (stdio, HTTP, SSE) with built-in Spring Security integration for role-based access control and audit logging
  • Includes reusable prompt templates using @PromptTemplate , dynamic tool registration, mu
skill.md

Spring AI MCP Server Implementation Patterns

Implements MCP servers with Spring AI for AI function calling, tool handlers, and MCP transport configuration.

Overview

Production-ready MCP server patterns: @Tool functions, @PromptTemplate resources, and stdio/HTTP/SSE transports with Spring AI security.

When to Use

MCP servers, Spring AI function calling, AI tools, tool calling, custom tool handlers, Spring Boot MCP, resource endpoints, or MCP transport configuration.

Quick Reference

Core Annotations

Annotation Target Purpose
@EnableMcpServer Class Enable MCP server auto-configuration
@Tool(description) Method Declare AI-callable tool
@ToolParam(value) Parameter Document tool parameter for AI
@PromptTemplate(name) Method Declare reusable prompt template
@PromptParam(value) Parameter Document prompt parameter

Transport Types

Transport Use Case Config
stdio Local process / Claude Desktop Default
http Remote HTTP clients port, path
sse Real-time streaming clients port, path

Key Dependencies

<!-- Maven -->
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-mcp-server</artifactId>
    <version>1.0.0</version>
</dependency>
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-starter-model-openai</artifactId>
    <version>1.0.0</version>
</dependency>
// Gradle
implementation 'org.springframework.ai:spring-ai-mcp-server:1.0.0'
implementation 'org.springframework.ai:spring-ai-starter-model-openai:1.0.0'

Instructions

1. Project Setup

Add Spring AI MCP dependencies (see Quick Reference above), configure the AI model in application.properties, and enable MCP with @EnableMcpServer:

@SpringBootApplication
@EnableMcpServer
public class MyMcpApplication {
    public static void main(String[] args) {
        SpringApplication.run(MyMcpApplication.class, args);
    }
}
spring.ai.openai.api-key=${OPENAI_API_KEY}
spring.ai.mcp.enabled=true
spring.ai.mcp.transport.type=stdio

2. Define Tools

Annotate methods with @Tool inside @Component beans. Use @ToolParam to document parameters:

@Component
public class WeatherTools {

    @Tool(description = "Get current weather for a city")
    public WeatherData getWeather(@ToolParam("City name") String city) {
        return weatherService.getCurrentWeather(city);
    }

    @Tool(description = "Get 5-day forecast for a city")
    public ForecastData getForecast(
            @ToolParam("City name") String city,
            @ToolParam(value = "Unit: celsius or fahrenheit", required = false) String unit) {
        return weatherService.getForecast(city, unit != null ? unit : "celsius");
    }
}

See references/implementation-patterns.md for database tools, API integration tools, and the FunctionCallback low-level pattern.

3. Create Prompt Templates

@Component
public class CodeReviewPrompts {

    @PromptTemplate(
        name = "java-code-review",
        description = "Review Java code for best practices and issues"
    )
    public Prompt createCodeReviewPrompt(
            @PromptParam("code") String code,
            @PromptParam(value = "focusAreas", required = false) List<String> focusAreas) {

        String focus = focusAreas != null ? String.join(", ", focusAreas) : "general best practices";
        return Prompt.builder()
                .system("You are an expert Java code reviewer with 20 years of experience.")
                .user("Review the following Java code for " + focus + ":\n```java\n" + code + "\n```")
                .build();
    }
}

See references/implementation-patterns.md for additional prompt template patterns.

4. Configure Transport

spring:
  ai:
    mcp:
      enabled: true
      transport:
        type: stdio       # stdio | http | sse
        http:
          port: 8080
          path: /mcp
      server:
        name: my-mcp-server
        version: 1.0.0

5. Add Security

@Configuration
public class McpSecurityConfig {

    @Bean
    public ToolFilter toolFilter(SecurityService securityService) {
        return (tool, context) -> {
            User user = securityService.getCurrentUser();
            if (tool.name().startsWith("admin_")) {
                return user.hasRole("ADMIN");
            }
            return securityService.isToolAllowed(user, tool.name());
        };
    }
}

Use @PreAuthorize("hasRole('ADMIN')") on tool methods for method-level security. See references/implementation-patterns.md for full security patterns.

6. Testing

@SpringBootTest
class WeatherToolsTest {

    @Autowired
    private WeatherTools weatherTools;

    @MockBean
    private WeatherService weatherService;

    @Test
    void testGetWeather_Success() {
        when(weatherService.
how to use spring-ai-mcp-server-patterns

How to use spring-ai-mcp-server-patterns on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add spring-ai-mcp-server-patterns
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill spring-ai-mcp-server-patterns

The skills CLI fetches spring-ai-mcp-server-patterns from GitHub repository giuseppe-trisciuoglio/developer-kit and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/spring-ai-mcp-server-patterns

Reload or restart Cursor to activate spring-ai-mcp-server-patterns. Access the skill through slash commands (e.g., /spring-ai-mcp-server-patterns) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.530 reviews
  • Aditi Kapoor· Dec 24, 2024

    Useful defaults in spring-ai-mcp-server-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aditi Bansal· Nov 15, 2024

    spring-ai-mcp-server-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Sakshi Patil· Nov 11, 2024

    Keeps context tight: spring-ai-mcp-server-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kabir Liu· Oct 6, 2024

    spring-ai-mcp-server-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Chaitanya Patil· Oct 2, 2024

    We added spring-ai-mcp-server-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Mia Gill· Sep 13, 2024

    spring-ai-mcp-server-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Hiroshi Abbas· Sep 9, 2024

    Useful defaults in spring-ai-mcp-server-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Piyush G· Sep 5, 2024

    spring-ai-mcp-server-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Mateo Haddad· Sep 5, 2024

    Keeps context tight: spring-ai-mcp-server-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Hiroshi Verma· Aug 28, 2024

    Registry listing for spring-ai-mcp-server-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.

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