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Glama

架构

vision.py    眼睛: 截屏 -> 降采样 -> Ollama VLM -> 坐标/问答      (跨平台)
hand/        手:   win32(user32) | x11(XTest) | macos(Quartz)   (平台后端分发)
agent.py     脑干: 闭环 + 步骤解释器 + 焦点等待 + 容差自愈
bench.py     度量: 任务 YAML(含 setup/teardown) -> 成功率报告
planner.py   规划: 目标 -> 步骤 JSON(本地模型,云 API 适配器预留)
mcp_server.py 插件: MCP stdio server,9 工具,协议一致性 CI 验证

Related MCP server: atomic-computer-mcp

快速开始

git clone https://github.com/ZYYDI1959/winagent-lite && cd winagent-lite
python -m venv .venv && .venv/Scripts/pip install -e .
# 需要本机 Ollama(默认模型 qwen2.5vl:7b)
cp config.example.yaml config.yaml

winagent doctor                          # 环境自检(一条命令诊断一切)
winagent look "任务栏右下角的时钟"         # 眼睛:FOUND x,y
winagent click 1824 1056                 # 手:真实点击
winagent run scenarios/notepad_save.yaml # 闭环:YAML 步骤
winagent bench                           # 评测:全任务成功率报告
winagent plan "打开记事本输入你好并保存"     # 规划:目标 -> 步骤
winagent-mcp                             # 以 MCP 插件模式运行

作为 MCP 插件使用(30 秒接入)

{ "mcpServers": { "winagent": {
    "command": "D:\\winagent-lite\\.venv\\Scripts\\python.exe",
    "args": ["-m", "winagent.mcp_server"] } } }

Final must have:

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