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 browseros-ai · MCP Server · ★ 13.8k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is BrowserOS safe to install? View the security audit →
<img alt="BrowserOS neo - The Missing Browser for Claude, Cowork & Codex | Product Hunt" width="250" height="54" src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?postid=1031913&theme=light&t=
| Stars | 13,802 |
| Forks | 1,470 |
| Language | TypeScript |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 62.1197821695142/100 |
| Open Issues | 90 |
| Last Updated | 2026-10-03 |
| Created | 2025-05-18 |
| Platforms | browser, claude-code, mcp, node |
| Est. Tokens | ~17k |
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BrowserOS is 🌐 The open-source Agentic browser; alternative to ChatGPT Atlas, Perplexity Comet, Dia.. It is categorized as a MCP Server with 13.8k GitHub stars.
BrowserOS is primarily written in TypeScript. It covers topics such as agent, ai-agents, automation.
You can find installation instructions and usage details in the BrowserOS GitHub repository at github.com/browseros-ai/BrowserOS. The project has 13.8k stars and 1470 forks, indicating an active community.
BrowserOS is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to BrowserOS on Agent Skills Hub include nanobrowser, bytebot, cursor-talk-to-figma-mcp. 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: