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Arthas

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MCP server for Java application diagnostics and performance analysis using Arthas integration

Arthas MCP Server

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Java diagnostics MCP server

Overview

Arthas MCP Server is an MCP-based diagnostic toolkit for Java applications, designed for LLM integration. It integrates with Alibaba Arthas so AI assistants can analyze and diagnose Java apps.

Features

  • Intelligent diagnostics via LLM-friendly tools
  • Real-time monitoring: JVM, threads, memory
  • Performance analysis: CPU usage, call tracing, bottlenecks
  • Runtime operations: dynamic class/method tools

Quick Start

Requirements

  • Python 3.13+
  • A running Java application
  • Arthas 3.6.7+

Install

uv sync

Run

python main.py

MCP Tools

  • connect_arthas: connect to Arthas WebConsole
  • get_connection_status: get current status
  • disconnect_arthas: disconnect
  • get_jvm_info: JVM info
  • get_thread_info: thread status and performance
  • get_memory_info: memory usage and GC
  • execute_arthas_command: run custom Arthas command
  • analyze_performance: performance analysis
  • trace_method_calls: method call tracing

Config

Add to Cursor / Claude Code

macOS: ~/.cursor/mcp.json Windows: C:\Users\{username}\.cursor\mcp.json

{ "mcpServers": { "arthas": { "command": "uv", "args": ["--directory", "F:\\path\\to\\arthas_mcp_server", "run", "python", "main.py"], "env": { "ARTHAS_URL": "http://localhost:8563" } } } }

Start Arthas

ARTHAS_URL: http://localhost:8563

curl -O https://arthas.aliyun.com/arthas-boot.jar java -jar arthas-boot.jar

Project Structure

arthas_mcp_server/
├── src/
│   ├── __init__.py
│   ├── models.py
│   ├── server.py
│   └── client.py
├── main.py
├── pyproject.toml
└── README.md

Development

uv sync --extra dev

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