by SDLLL · MCP Server · ★ 68
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-for-safari safe to install? View the security audit →
Claude for Safari Give your AI Agent the power to control Safari Website · Quick Start · Features · FAQ English | 中文 Why This? You want your AI Agent to help with browser tasks — then you discover: 🔒 Playwright → Separate browser instance, hijacks your session 🧩 Claude for Chrome → Requires Chrome extension, doesn't work with Safari 📝 Copy & paste → Manually feeding page content to AI every time You just want AI to use your Safari, as if you were doing it yourself. Claude for Safari makes it one command: After installing, tell Claude "check what's open in my Safari" — it reads and controls your real browser directly. If this saves
npx skills add SDLLL/claude-for-safariTaken from the project's README on GitHub. Check the security audit before running it.
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 →
| Stars | 68 |
| Forks | 10 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 58.5601173248144/100 |
| Last Updated | 2026-08-04 |
| Created | 2026-02-28 |
| Platforms | browser, claude-code, mcp, node |
| Est. Tokens | ~3k |
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claude-for-safari is Give your AI Agent the power to control Safari on macOS. No extensions, no separate browser.. It is categorized as a MCP Server with 68 GitHub stars.
claude-for-safari is primarily written in JavaScript. It covers topics such as ai-agent, applescript, browser-automation.
The README on GitHub (github.com/SDLLL/claude-for-safari) gives: npx skills add SDLLL/claude-for-safari. Usage details are in the same README.
claude-for-safari is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to claude-for-safari on Agent Skills Hub include safari-mcp, MCPSafari, google-ai-mode-skill. 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: