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 DevinoSolutions · MCP Server · ★ 25
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is stealth-chrome-devtools-mcp safe to install? View the security audit →
Undetectable browser automation for AI agents via MCP. Stealth Chrome DevTools with smart profile management, anti-detection arg filtering, and CDP access.
| Stars | 25 |
| Forks | 4 |
| Language | Python |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 72.7095247669367/100 |
| Open Issues | 13 |
| Last Updated | 2026-10-01 |
| Created | 2026-05-14 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~18k |
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stealth-chrome-devtools-mcp is Undetectable browser automation for AI agents via MCP. Stealth Chrome DevTools with smart profile management, anti-detection arg filtering, and CDP access.. It is categorized as a MCP Server with 25 GitHub stars.
stealth-chrome-devtools-mcp is primarily written in Python. It covers topics such as anti-detection, browser-automation, cdp.
You can find installation instructions and usage details in the stealth-chrome-devtools-mcp GitHub repository at github.com/DevinoSolutions/stealth-chrome-devtools-mcp. The project has 25 stars and 4 forks, indicating an active community.
stealth-chrome-devtools-mcp is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to stealth-chrome-devtools-mcp on Agent Skills Hub include neobrowser, camofox-mcp, native-devtools-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: