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 JacobJandon · MCP Server · ★ 64
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is OnionClaw safe to install? View the security audit →
OnionClaw 🧅 by JacobJandon OpenClaw skill + standalone tool — full Tor / dark web access for AI agents OnionClaw gives AI agents full access to the Tor network and .onion hidden services. It runs as an OpenClaw skill (drop-in, zero config beyond a file) and also works standalone from any terminal. Based on the SICRY engine — 18 dark web search engines, Robin OSINT pipeline, four LLM analysis modes. ⚠️ The Rabbit Hole Autonomous agents paired with the Tor network will be one of the most dangerous automation stacks on the internet within the next five
| Stars | 64 |
| Forks | 7 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 69.2034190116238/100 |
| Open Issues | 6 |
| Last Updated | 2026-07-01 |
| Created | 2026-03-14 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~98k |
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OnionClaw is OnionClaw™ — OpenClaw skill for full Tor dark web access: search .onion sites, fetch hidden services, rotate identity, run OSINT pipeline, craw.. It is categorized as a MCP Server with 64 GitHub stars.
OnionClaw is primarily written in Python. It covers topics such as ai-agents, dark-web, hidden-services.
You can find installation instructions and usage details in the OnionClaw GitHub repository at github.com/JacobJandon/OnionClaw. The project has 64 stars and 7 forks, indicating an active community.
The top alternatives to OnionClaw on Agent Skills Hub include OnionClaw, zettelforge, bottube. 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: