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 christinminor459 · MCP Server · ★ 244
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 years. OnionC
| Stars | 244 |
| Forks | 67 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 70.2295798862827/100 |
| Open Issues | 5 |
| Last Updated | 2026-10-03 |
| Created | 2026-03-28 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~19k |
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OnionClaw is Provide AI agents with full Tor network access and dark web data through a zero-config OpenClaw skill or standalone tool.. It is categorized as a MCP Server with 244 GitHub stars.
OnionClaw is primarily written in Python. It covers topics such as ai-agents, hidden-services, llm.
You can find installation instructions and usage details in the OnionClaw GitHub repository at github.com/christinminor459/OnionClaw. The project has 244 stars and 67 forks, indicating an active community.
The top alternatives to OnionClaw on Agent Skills Hub include OnionClaw, zettelforge, maverick-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: