{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_v6hayuwhr28t","handle":"iflow-mcp-toby1123yjh-arthas-mcp-server","url":"https://wellknown.network/agents/iflow-mcp-toby1123yjh-arthas-mcp-server","links":{"self":"https://wellknown.network/agents/iflow-mcp-toby1123yjh-arthas-mcp-server/record.json","html":"https://wellknown.network/agents/iflow-mcp-toby1123yjh-arthas-mcp-server","markdown":"https://wellknown.network/agents/iflow-mcp-toby1123yjh-arthas-mcp-server/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-toby1123yjh-arthas-mcp-server","status":"https://wellknown.network/api/v1/agents/iflow-mcp-toby1123yjh-arthas-mcp-server/status","claim":"https://wellknown.network/agents/iflow-mcp-toby1123yjh-arthas-mcp-server/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-toby1123yjh-arthas-mcp-server/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-toby1123yjh-arthas-mcp-server/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-toby1123yjh-arthas-mcp-server/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-toby1123yjh-arthas-mcp-server/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-toby1123yjh-arthas-mcp-server","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_toby1123yjh-arthas-mcp-server","summary":"Java Performance Analysis & Diagnostics - LLM-powered MCP Server for real-time monitoring, memory analysis, thread profiling, and system optimization","description":"# Arthas MCP Server\n\n[![中文](https://img.shields.io/badge/lang-中文-blue.svg)](README.zh-CN.md)\n\nJava diagnostics MCP server\n\n## Overview\n\nArthas 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.\n\n## Features\n\n- Intelligent diagnostics via LLM-friendly tools\n- Real-time monitoring: JVM, threads, memory\n- Performance analysis: CPU usage, call tracing, bottlenecks\n- Runtime operations: dynamic class/method tools\n- exmaple \n![示例图片](./usecase/case1.jpg)\n\n## Quick Start\n\n### Install\n```bash\nuv sync\n```\n\n### Run\n```bash\npython main.py\n```\n\n## MCP Tools\n\n- connect_arthas: connect to Arthas WebConsole\n- get_connection_status: get current status\n- disconnect_arthas: disconnect\n- get_jvm_info: JVM info\n- get_thread_info: thread status and performance\n- get_memory_info: memory usage and GC\n- execute_arthas_command: run custom Arthas command\n- analyze_performance: performance analysis\n- trace_method_calls: method call tracing\n\n## Config\n\n### Add to Cursor / Claude Code\n\nmacOS: `~/.cursor/mcp.json`\nWindows: `C:\\Users\\{username}\\.cursor\\mcp.json`\n\n```json\n{\n  \"mcpServers\": {\n    \"arthas\": {\n      \"command\": \"uv\",\n      \"args\": [\"--directory\", \"F:\\\\path\\\\to\\\\arthas_mcp_server\", \"run\", \"python\", \"main.py\"],\n      \"env\": { \"ARTHAS_URL\": \"http://localhost:8563\" }\n    }\n  }\n}\n```\n\n### Start Arthas\n\nThere are multiple deployment methods: either attach mode or agent mode. Both approaches ultimately result in listening for HTTP requests (Arthas commands) on port 8563.\n\n## Project Structure\n\n```\narthas_mcp_server/\n├── src/\n│   ├── __init__.py\n│   ├── models.py\n│   ├── server.py\n│   └── client.py\n├── main.py\n├── pyproject.toml\n└── README.md\n```\n\n## Development\n\n```bash\nuv sync --extra dev\n```","publisher":null,"homepage":"https://github.com/arthas-mcp/arthas-mcp-server","repository":"https://github.com/arthas-mcp/arthas-mcp-server","version":"0.1.0","license":"MIT","protocols":["mcp"],"tags":["analysis","arthas","diagnostics","java","llm","mcp","monitoring","optimization","performance","profiling"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_toby1123yjh-arthas-mcp-server","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"dev.monitoring","name":"Monitoring & Observability","confidence":1,"provenance":"declared"}],"categories":["dev"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp_toby1123yjh-arthas-mcp-server","registry":"pypi","observedAt":"2026-09-15T20:21:30.251Z","publishedAt":"2026-02-08T12:20:47.628519Z","latestVersion":"0.1.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_toby1123yjh-arthas-mcp-server","url":"https://pypi.org/project/iflow-mcp_toby1123yjh-arthas-mcp-server/","firstSeenAt":"2026-09-09T21:24:28.991Z","fetchedAt":"2026-09-15T20:20:12.543Z","normalizedAt":"2026-09-15T20:20:12.543Z"}]},"firstSeenAt":"2026-09-09T21:24:28.991Z","updatedAt":"2026-09-15T20:21:30.251Z"}