mcpField
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java-sdk

java-sdk

Local
github.com/lxwhappyDeveloper Tools0Updated 73w ago
Repository

About java-sdk

The official Java SDK for integrating Java applications with the Model Context Protocol, maintained in collaboration with Spring AI. It supports both client and server development and synchronous or asynchronous communication.

Key features

  1. 01Java SDK for MCP integration
  2. 02Client and server development
  3. 03Synchronous communication
  4. 04Asynchronous communication
  5. 05Spring AI integration

Use cases

  1. 01Building Java MCP clients
  2. 02Implementing MCP servers in Java
  3. 03Adding MCP support to Spring AI applications

MCP support

The SDK provides Java integration for building MCP clients and servers. Spring AI extends it with Spring Boot client and server starters.

#jetbrain#java-sdk#ai-integration

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "java-sdk": {
      "command": "npx",
      "args": [
        "-y",
        "@jetbrains/mcp-proxy"
      ]
    }
  }
}
Run commandnpx -y @jetbrains/mcp-proxy

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@jetbrains/mcp-proxy

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Java SDK

Build Status

A set of projects that provide Java SDK integration for the Model Context Protocol. This SDK enables Java applications to interact with AI models and tools through a standardized interface, supporting both synchronous and asynchronous communication patterns.

📚 Reference Documentation

MCP Java SDK documentation

For comprehensive guides and SDK API documentation, visit the MCP Java SDK Reference Documentation.

Spring AI MCP documentation

Spring AI MCP extends the MCP Java SDK with Spring Boot integration, providing both client and server starters. Bootstrap your AI applications with MCP support using Spring Initializer.

Development

Building from Source
./mvnw clean install -DskipTests
Running Tests

To run the tests you have to pre-install Docker and npx.

./mvnw test

Contributing

Contributions are welcome! Please follow the Contributing Guidelines.

Team

  • Christian Tzolov
  • Dariusz Jędrzejczyk

Links

License

This project is licensed under the MIT License.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.