spring-ai-mcp-server-patterns

MCP servers with Spring AI use declarative patterns via @Tool, @ToolParam, and @PromptTemplate annotations to expose tools, resources, and prompts. Enable the server with @EnableMcpServer, configure HTTP or stdio transport, and Spring AI handles the MCP protocol binding and function calling integration automatically.

Yes. Spring AI MCP servers are designed for production Spring Boot environments. They integrate with Spring Security for authentication, support monitoring instrumentation, and follow declarative patterns that fit standard enterprise architectures requiring external tool integration and function calling capabilities.

Spring AI MCP servers support both HTTP and stdio transports. Choose HTTP for service-to-service communication over the network, or stdio for local process communication. Configure transport during MCP server bootstrap to match your deployment topology and integration requirements.

Use @PromptTemplate annotations to define reusable prompt templates within your MCP server. Combine with @Tool-annotated methods to create resources and tools. Spring AI standardizes transport and discovery patterns, enabling clients to query available prompts, tools, and resources through the MCP protocol.

No. Spring AI MCP servers handle function calling through declarative @Tool and @ToolParam annotations. The framework manages serialization, parameter binding, and MCP protocol compliance, eliminating boilerplate and reducing the surface area for errors in tool invocation.

Stdio transport is lightweight and suitable for local process integration but limited to single-machine communication. HTTP transport enables remote service-to-service calls and horizontal scaling but introduces network latency and requires transport security configuration. Choose based on deployment topology and security posture.