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Spring-AI-MCP
Java SDK para el Protocolo de contexto del modelo (MCP), que proporciona una integración perfecta entre las aplicaciones Java y Spring y los modelos y herramientas de IA compatibles con MCP.
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NOTE: This project has been graduated and moved to the MCP Java SDK and Spring AI MCP. See you there! This repository is now archived.
Java & Spring MCP
Set of projects that provide Java SDK and Spring Framework integration for the Model Context Protocol. It enables Java applications to interact with AI models and tools through a standardized interface, supporting both synchronous and asynchronous communication patterns.
📚 Reference Documentation
For comprehensive guides and API documentation, visit the Spring AI MCP Reference Documentation.


Projects
MCP Java SDK
Java implementation of the Model Context Protocol specification. It includes:
- Synchronous and asynchronous MCP Client and MCP Server implementations
- Standard MCP operations support (tool discovery, resource management, prompt handling, structured logging). Support for request and notification handling.
- Stdio and SSE transport implementations.
MCP Transports
Core Transports
- Stdio-based (
StdioClientTransport
,StdioServerTransport
) for process-based communication - Java HttpClient-based SSE client (
HttpClientSseClientTransport
) for HTTP streaming - Servlet-based SSE server (
HttpServletSseServerTransport
) for HTTP SSE Server streaming using traditional Servlet API
Optional SSE Transports
- WebFlux SSE Transport - Reactive HTTP streaming with Spring WebFlux (Client & Server)
-
WebMvc SSE Transport - Spring MVC based HTTP SSE transport (Server only).
You can use the core
HttpClientSseClientTransport
transport as a SSE client.
Spring AI MCP
The Spring integration module provides Spring-specific functionality:
- Integration with Spring AI's function calling system
- Spring-friendly abstractions for MCP clients
- Auto-configurations (WIP)
Installation
Add the following dependencies to your Maven project:
<!-- Core MCP -->
<dependency>
<groupId>org.springframework.experimental</groupId>
<artifactId>mcp</artifactId>
</dependency>
<!-- Optional: WebFlux SSE transport -->
<dependency>
<groupId>org.springframework.experimental</groupId>
<artifactId>mcp-webflux-sse-transport</artifactId>
</dependency>
<!-- Optional: WebMVC SSE transport -->
<dependency>
<groupId>org.springframework.experimental</groupId>
<artifactId>mcp-webmvc-sse-transport</artifactId>
</dependency>
<!-- Optional: Spring AI integration -->
<dependency>
<groupId>org.springframework.experimental</groupId>
<artifactId>spring-ai-mcp</artifactId>
</dependency>
This is a milestone release, not available on Maven Central. Add this repository to your POM:
<repositories>
<repository>
<id>spring-milestones</id>
<name>Spring Milestones</name>
<url>https://repo.spring.io/milestone</url>
<snapshots>
<enabled>false</enabled>
</snapshots>
</repository>
</repositories>
Reffer to the Dependency Management page for more information.
Example Demos
Explore these MCP examples in the spring-ai-examples/model-context-protocol repository:
- SQLite Simple - Demonstrates LLM integration with a database
- SQLite Chatbot - Interactive chatbot with SQLite database interaction
- Filesystem - Enables LLM interaction with local filesystem folders and files
- Brave - Enables natural language interactions with Brave Search, allowing you to perform internet searches.
- Theme Park API Example - Shows how to create an MCP server and client with Spring AI, exposing Theme Park API tools
- Http SSE Client + WebMvc SSE Server - Showcases how to create and use MCP WebMvc servers and HttpClient clients with different capabilities.
- WebFlux SSE Client + WebFlux SSE Server - Showcases how to create and use MCP WebFlux servers and clients with different capabilities
- HttpClient SSE Client + Servlet SSE Server - Showcases how to create and use MCP Servlet SSE Server and HttpClient SSE Client with different capabilities
Documentation
Development
- Building from Source
mvn clean install
- Running Tests
mvn test
Contributing
This is an experimental Spring project. Contributions are welcome! Please:
- Fork the repository
- Create a feature branch
- Submit a Pull Request
Team
- Christian Tzolov
- Dariusz Jędrzejczyk
Links
License
This project is licensed under the Apache License 2.0.
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Reviews

user_EihCSbEM
As a dedicated user of Spring-AI-MCP, I am thoroughly impressed by its capabilities. The seamless integration and intuitive features truly enhance my AI projects. The author's focus on delivering a reliable and efficient framework is evident. Highly recommend for anyone looking to streamline their machine learning workflows. Fantastic work by Spring-Projects-Experimental!