MCP Performance Analyzer
Monitors and analyzes mobile application performance data to detect severe issues such as excessive memory usage and view count growth. Provides intelligent analysis with customizable rules and integrates seamlessly with development workflows.
README
🚀 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
🌐 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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