JVM MCP Server
About
This is an implementation project of a JVM-based MCP (Model Context Protocol) server. The project aims to provide a standardized MCP server implementation for the JVM platform, enabling AI models to better interact with the Java ecosystem.
Details
- Author
- xzq-xu
- GitHub stars
- 87
- Downloads
- 304
- Categories
- Developer Tools, Other, Infrastructure
Jump to
- Zero external dependencies – uses only native JDK tools
- Lightweight and minimal resource consumption
- Non‑intrusive: no modifications to target applications
- Supports both local and remote JVM monitoring via SSH
- Provides advanced diagnostics: method tracing, decompilation, logger control
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
JVM MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install with pip install jvm-mcp-server or uv pip install jvm-mcp-server. Start the server locally with uv run jvm-mcp-server or via Python using JvmMcpServer().run(). For remote JVMs, set SSH environment variables (e.g., SSH_HOST, SSH_PORT) and run with --env-file .env. Integrate with an MCP client by adding a configuration entry using the uv command and the jvm-mcp-server tool name.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"jvm mcp server": {
"jvm-mcp-server": {
"command": "uv",
"args": [
"pip",
"install",
"jvm-mcp-server"
]
}
}
}
}McpServers
{
"jvm-mcp-server": {
"command": "uv",
"args": [
"pip",
"install",
"jvm-mcp-server"
]
}
}JVM MCP Server
<p align="center">
</p>
A lightweight JVM monitoring and diagnostic MCP (Multi-Agent Communication Protocol) server implementation based on native JDK tools. Provides AI agents with powerful capabilities to monitor and analyze Java applications without requiring third-party tools like Arthas.
<a href="https://glama.ai/mcp/servers/@xzq-xu/jvm-mcp-server">
</a>
Hosted deployment
A hosted deployment is available on Fronteir AI.
Features
- Zero Dependencies: Uses only native JDK tools (jps, jstack, jmap, etc.)
- Lightweight: Minimal resource consumption compared to agent-based solutions
- High Compatibility: Works with all Java versions and platforms
- Non-Intrusive: No modifications to target applications required
- Secure: Uses only JDK certified tools and commands
- Remote Monitoring: Support for both local and remote JVM monitoring via SSH
Core Capabilities
Basic Monitoring
- Java process listing and identification - JVM basic information retrieval - Memory usage monitoring - Thread information and stack trace analysis - Class loading statistics - Detailed class structure informationAdvanced Features
- Method call path analysis - Class decompilation - Method search and inspection - Method invocation monitoring - Logger level management - System resource dashboardSystem Requirements
- Python 3.6+
- JDK 8+
- Linux/Unix/Windows OS
- SSH access (for remote monitoring)
Installation
Using uv (Recommended)
```bash
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