No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by CatCatUncle · MCP Server · ★ 227
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openworkbuddy safe to install? View the security audit →
OpenWorkBuddy 一个真吐文件的本机 AI 办公 agent。 说一句人话,它自己规划、动手、验收——交给你的是能直接打开的 PPT / Word / Excel / 网页,不是一段聊天记录。 A local-first AI office agent that hands you files, not chat logs. → English README ⚡ 30 秒跑起来 · 下载安装包 · 最新动态 · 飞书交流群 · 功能清单 ⭐ 觉得有用就点个 Star —— 这个项目没有推广预算,能不能被搜到,基本取决于这个数字。
| Stars | 227 |
| Forks | 57 |
| Language | JavaScript |
| Category | MCP Server |
| Quality Score | 58.2127367244563/100 |
| Open Issues | 6 |
| Last Updated | 2026-10-02 |
| Created | 2026-08-10 |
| Platforms | claude-code, cli, codex, mcp, node |
| Est. Tokens | ~14k |
These tools work well together with openworkbuddy for enhanced workflows:
Looking for a openworkbuddy alternative? If you're comparing openworkbuddy with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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从 0 复刻 WorkBuddy-style 桌面 AI 助手 Harness:24 章 Python 教程,覆盖 Agent Loop、工具调用、记忆系统、Sidecar、沙盒审计、DeepSeek/OpenAI 评测
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openworkbuddy is Open-source Claude Cowork / Codex / WorkBuddy alternative — a local-first AI office agent that turns one request into real PPTX, DOCX, XLSX and HTML files. Runs DeepSeek, Qwen, Doubao, Claude or Ollam. It is categorized as a MCP Server with 227 GitHub stars.
openworkbuddy is primarily written in JavaScript. It covers topics such as agent-harness, ai-agent, ai-office-agent.
You can find installation instructions and usage details in the openworkbuddy GitHub repository at github.com/CatCatUncle/openworkbuddy. The project has 227 stars and 57 forks, indicating an active community.
The top alternatives to openworkbuddy on Agent Skills Hub include comfyui-mcp, hunter-community, CluxMate. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: