What is MCP?
MCP follows a client‑server architecture. The Host is the main application integrating an LLM; Clients maintain 1:1 connections with Servers; Servers expose tools, resources, and capabilities to clients.
Spring AI integration with MCP (MCP)
@kuldeepsingh99
Basic information
About Spring AI integration with MCP
Build your own mcp server with spring ai
Spring AI integration with MCP config
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositorySpring AI integration with MCP tools
Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Spring AI integration with MCP (Model Context Protocol)?
Spring AI MCP extends the MCP Java SDK with Spring Boot integration, providing both client and server starters. It enables AI models to interact with external tools and resources in a standardized way through the Model Context Protocol (MCP).
How to use Spring AI integration with MCP (Model Context Protocol)?
Bootstrap your AI applications with MCP support using Spring Initializer. The example shows an MCP Server connecting to a PostgreSQL database, exposing tools annotated with @Tool, and an MCP Client that connects to the server. The LLM (e.g., Ollama) automatically selects the correct tool based on the prompt when tool names and descriptions are properly written.
Key features of Spring AI integration with MCP (Model Context Protocol)
- Provides both MCP Client and MCP Server Spring Boot starters
- Supports stdio and SSE transport mechanisms
- Exposes tools via
@Tooland@ToolParamannotations - Automates LLM tool selection based on prompt and tool metadata
- Integrates with Spring Data repositories for database queries
Use cases of Spring AI integration with MCP (Model Context Protocol)
- Let an AI assistant query a PostgreSQL database by matching prompts to predefined search tools
- Build a server that offers multiple data‑access tools (e.g., by name, by owner) for an LLM
- Create a client that connects to an MCP server and delegates tool invocation to an LLM
- Prototype an AI‑powered customer support agent that fetches account information from a database
Frequently asked questions
What transport mechanisms does Spring AI MCP support?
It supports Standard Input/Output (stdio) for local process communication and Server‑Sent Events (SSE) for HTTP‑based communication.
What tools are exposed in the example?
The example exposes two tools: “Search Seller account by name” and “Find all Seller Accounts by owner”, both querying a PostgreSQL `seller_account` table.
How does the LLM choose which tool to call?
The LLM automatically selects the correct tool based on the prompt. Tool names and descriptions must be written clearly for proper matching.
What are the runtime requirements for the example?
Java (Spring Boot), the MCP server and client projects, a PostgreSQL database (run via Docker), and a local LLM (e.g., Ollama with any model) are required.
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