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DaSheng1994

MCP Performance Analyzer

by DaSheng1994

🚀 MCP性能分析服务器

移动应用性能监控数据智能分析工具,专注于严重问题检测

📋 快速开始

1. 获取项目

git clone git@github.com:DaSheng1994/mcp_analyze_quality.git
cd mcp_analyze_quality

2. 安装依赖

# 创建虚拟环境
python3 -m venv .venv
source .venv/bin/activate  # Linux/macOS

# 安装依赖
pip install -r requirements.txt

3. 配置Cursor MCP

编辑 ~/.cursor/mcp.json

{
  "mcpServers": {
    "performance-analyzer": {
      "command": "/path/to/your/project/.venv/bin/python",
      "args": ["/path/to/your/project/main.py"],
      "cwd": "/path/to/your/project"
    }
  }
}

4. 重启Cursor并使用

完全退出并重新启动Cursor,然后在对话中输入:

分析这个性能数据:http://localhost:8000/meminfo.csv

Related MCP server: ClipSense MCP Server

🌐 远程部署

服务器端部署

# 在服务器上部署
git clone git@github.com:DaSheng1994/mcp_analyze_quality.git
cd mcp_analyze_quality
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

# 启动服务(后台运行)
nohup python main.py > mcp.log 2>&1 &
nohup python3 -m http.server 8000 > http.log 2>&1 &

客户端配置

团队成员在各自的Cursor中配置:

{
  "mcpServers": {
    "performance-analyzer": {
      "command": "ssh",
      "args": ["your-server", "cd /path/to/mcp_analyze_quality && .venv/bin/python main.py"],
      "env": {}
    }
  }
}

使用远程服务

分析这个性能数据:http://your-server-ip:8000/meminfo.csv

📊 功能特性

  • 严重问题检测: 专注于识别需要立即处理的严重性能问题

  • 简洁输出: 只返回严重警告信息,避免信息过载

  • 智能分析: 基于预定义规则进行精准判断

  • 易于集成: 轻量级MCP服务器,快速部署

🚨 严重警告规则

当前支持的严重警告检测:

  • 物理内存警告: VmRSS超过1.3GB时触发

  • Views数量警告: Views增长超过700个时触发

📝 自定义规则

可以通过修改 .cursor/rules/quality-rules.mdc 文件来自定义分析规则。


🚀 现在就开始使用MCP性能分析工具吧!

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