MCP Scaffold

Turn your Spring Data repositories into AI-ready MCP tools

MCP Scaffold analyzes your existing Spring Boot application and generates @McpTool-annotated wrapper classes that expose your repositories and services to AI assistants via the Model Context Protocol.

Documentation

Guide	Description
Getting Started	Step-by-step setup guide
Configuration Reference	All YAML options explained
How It Works	Architecture and internals

Why MCP Scaffold?

• Zero manual annotation — Works with your existing code, no changes required
• Smart descriptions — Auto-generated from Javadoc, method names, and entity metadata
• Read-only detection — Automatically identifies safe operations
• Regeneratable — Run again whenever your code changes

Quick Start

1. Add the plugin and dependencies

<dependencies>
    <!-- MCP Annotations (required for generated code) -->
    <dependency>
        <groupId>org.springaicommunity</groupId>
        <artifactId>mcp-annotations</artifactId>
        <version>0.7.0</version>
    </dependency>
    
    <!-- Spring AI MCP Server -->
    <dependency>
        <groupId>org.springframework.ai</groupId>
        <artifactId>spring-ai-starter-mcp-server-webmvc</artifactId>
    </dependency>
</dependencies>

<build>
    <plugins>
        <plugin>
            <groupId>io.github.arvindand</groupId>
            <artifactId>mcp-scaffold-maven-plugin</artifactId>
            <version>0.1.1</version>
            <executions>
                <execution>
                    <goals>
                        <goal>generate</goal>
                    </goals>
                </execution>
            </executions>
        </plugin>
    </plugins>
</build>

2. Generate configuration

mvn mcp-scaffold:suggest
mv mcp-scaffold-suggested.yaml mcp-scaffold.yaml

3. Build

mvn compile

Your MCP tools are generated in target/generated-sources/mcp — ready for AI assistants to use!

Full setup guide →

What Gets Generated?

Given this repository:

@Repository
public interface OwnerRepository extends JpaRepository<Owner, Long> {
    /**
     * Find owners by last name (case-insensitive, partial match).
     */
    List<Owner> findByLastNameContainingIgnoreCase(String lastName);
}

MCP Scaffold generates:

@Component
public class OwnerRepositoryMcpTools {

    @McpTool(
        name = "owner_find_by_last_name_containing_ignore_case",
        description = "Find owners by last name (case-insensitive, partial match). " +
                      "Returns Owner with: id, firstName, lastName, address, city, telephone. [Read-only]"
    )
    public List<Owner> findByLastNameContainingIgnoreCase(
        @McpToolParam(description = "The last name to search for", required = true) 
        String lastName
    ) {
        return ownerRepository.findByLastNameContainingIgnoreCase(lastName);
    }
}

The generated descriptions include:

• Javadoc comments
• Entity field information
• Enum values for enum parameters
• Read-only markers

See the petclinic example →

Configuration

Create mcp-scaffold.yaml in your project root (or use mvn mcp-scaffold:suggest to generate one):

mcp:
  scaffold:
    scan:
      packages:
        - com.example.repository
        - com.example.service
    filter:
      include-patterns:
        - "*Repository"
        - "*Service"
      exclude-methods:
        - flush
        - deleteAll
    descriptions:
      include-javadoc: true
      include-entity-fields: true
      include-enum-values: true

Full configuration reference →

Try It Out

The Petclinic example is a complete working demo you can run:

./mvnw clean install
./mvnw -pl mcp-scaffold-examples/petclinic-mcp spring-boot:run

Then connect Claude Desktop or any MCP client to http://localhost:8080/sse.

Full example with testing instructions →

Requirements

• Java 21 or later
• Maven 3.9+
• Spring Boot 3.x application
• Spring AI 1.1.0+ with MCP server starter

Building from Source

git clone https://github.com/arvindand/mcp-scaffold.git
cd mcp-scaffold
./mvnw clean install

License

Apache License 2.0 — see LICENSE for details.

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Author: Arvind Menon