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 OthmaneBlial · Agent Tool · ★ 8
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is FreeComputerUse safe to install? View the security audit →
Local-first AI browser automation with Playwright. Use OpenAI, Grok, DeepSeek, Anthropic and compatible APIs—or ChatGPT/Claude Code subscriptions. Approve site access, watch each action, and replay proven workflows with zero model calls.
| Stars | 8 |
| Forks | 1 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67.200149542479/100 |
| Last Updated | 2026-09-27 |
| Created | 2026-09-18 |
| Platforms | browser, claude-code, node |
| Est. Tokens | ~16k |
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FreeComputerUse is Local-first AI browser automation with Playwright. Use OpenAI, Grok, DeepSeek, Anthropic and compatible APIs—or ChatGPT/Claude Code subscriptions. Approve site access, watch each action, and replay pr. It is categorized as a Agent Tool with 8 GitHub stars.
FreeComputerUse is primarily written in TypeScript. It covers topics such as ai-agent, anthropic, browser-agent.
You can find installation instructions and usage details in the FreeComputerUse GitHub repository at github.com/OthmaneBlial/FreeComputerUse. The project has 8 stars and 1 forks, indicating an active community.
FreeComputerUse is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to FreeComputerUse on Agent Skills Hub include browser-mcp, brainstorm-mcp, hanzi-in-chrome. 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: