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 TurixAI · MCP Server · ★ 3.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is TuriX-CUA safe to install? View the security audit →
TuriX · Desktop Actions, Driven by AI Talk to your computer, watch it work. English | 中文 📞 Contact & Community Join our Discord community for support, discussions, and updates: Or contact us with email: contact@turix.ai TuriX lets your powerful AI models take real, hands‑on actions directly on your desktop. It ships with a state‑of‑the‑art computer‑use agent (achieves 80% success rate on our OSWorld‑style Mac benchmark and 64.2% success rate on OSWorld) yet stays 100 % open‑source and cost‑free for personal & research use. Prefer your own model? Change in and go. Table of Contents 📞 Contact & Community 🤖 OpenClaw Skill 📰 Latest News 🖼️ Demos ✨ Key Features 📊 Model Performance 🚀 Quick‑Start (macOS 15+) Download the App [2. Create a Python 3.12 Environment](#2-cre
| Stars | 3,161 |
| Forks | 328 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.1854709030341/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-14 |
| Created | 2025-08-04 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~17k |
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TuriX-CUA is This is the official website for TuriX Computer-use-Agent. It is categorized as a MCP Server with 3.2k GitHub stars.
TuriX-CUA is primarily written in Python. It covers topics such as agent, ai-agents, browser-use.
You can find installation instructions and usage details in the TuriX-CUA GitHub repository at github.com/TurixAI/TuriX-CUA. The project has 3.2k stars and 328 forks, indicating an active community.
TuriX-CUA is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to TuriX-CUA on Agent Skills Hub include bytebot, open-codex-computer-use, agent-desktop. 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: