Overview of MCP Annotations in Spring AI

The Model Context Protocol (MCP) has emerged as a standard for connecting AI models to external data and tools, offering a universal connector approach. Spring AI supports this protocol through a dedicated module introducing a declarative, annotation-based programming model, reducing the need for manual integration configuration.

Why This Matters

Traditional AI integration often requires complex, bespoke code for each data source, leading to maintainability issues and scalability bottlenecks. MCP aims to standardize this interaction, but implementing it manually can still be cumbersome; Spring AI’s annotations simplify this process, allowing developers to expose functionality with minimal boilerplate. The cost of failing to standardize AI integrations can quickly escalate, potentially requiring significant refactoring and increased development time as the number of connected systems grows.

Key Insights

Spring AI MCP features are currently in Milestone/Snapshot repositories (as of early 2026): Developers need to configure their Maven projects to access these pre-release artifacts.
@McpTool annotation defines executable “tools”: This annotation transforms Java methods into AI-callable actions, streamlining the integration process.
@McpResource enables data exposure as virtual files: This allows AI models to access data in a read-only format, similar to reading a file.

Working Example

@Service
public class CalculatorService {
    @McpTool(
        name = "calculate_sum",
        description = "Calculates the sum of two integers. Useful for basic arithmetic."
    )
    public int add(
        @McpToolParam(description = "The first number to add", required = true) int a,
        @McpToolParam(description = "The second number to add", required = true) int b
    ) {
        return a + b;
    }
}

Practical Applications

Customer Support Chatbot: A chatbot using Spring AI and MCP annotations could access a customer database via @McpResource to provide personalized support.
Code Review Tool: Developers could use @McpTool to create a code review service, enabling an AI agent to analyze code snippets and suggest improvements.

References:

https://www.baeldung.com/spring-ai-mcp-annotations

On This Page

Overview of MCP Annotations in Spring AI