Provide AI agents with full Tor network access and dark web data through a zero-config OpenClaw skill or standalone tool.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"onionclaw": {
"command": "<see-readme>",
"args": []
}
}
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Provide AI agents with full Tor network access and dark web data through a zero-config OpenClaw skill or standalone tool.
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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 .env 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.
# As an OpenClaw skill:
cp -r OnionClaw ~/.openclaw/skills/onionclaw
# → agent now has 7 dark web commands available in every session
# Standalone:
python3 check_tor.py # verify Tor
python3 search.py --query "ransomware healthcare"
python3 pipeline.py --query "acme.com data leak" --mode corporate
Autonomous agents paired with the Tor network will be one of the most dangerous automation stacks on the internet within the next five years. OnionClaw is living proof that the rabbit hole goes deeper than most people think.
This tool is built for legitimate OSINT, threat intelligence, and security research. But the same primitives — anonymous routing, bulk scraping, AI-driven synthesis, zero-attribution browsing, automated identity rotation — are precisely what make this combination genuinely dangerous in the wrong hands.
This is not a warning tucked in fine print. It is the whole point of writing it down openly.
| Use case | What it looks like |
|---|---|
| Dark-web crawling | Automated, headless spidering of .onion services at scale — forums, paste sites, markets, leak boards — with full identity rotation between every request. No human ever touches a keyboard. |
| Threat intelligence | Continuous monitoring of ransomware group blogs, initial access broker ads, CVE exploit drops, and actor chatter long before it surfaces on clearnet feeds. |
| Marketplace monitoring | Price tracking, stock alerts, vendor reputation scraping, and availability checks across darknet markets — the same logic a researcher uses to track fentanyl price trends is the same logic a supplier uses to undercut competitors. |
| Credential surveillance | Watching paste boards, breach dumps, and forum leaks for specific email domains, API keys, SSH keys, or internal hostnames the moment they appear — at a scale no human analyst can match. |
| Deanonymisation research | Cross-correlating .onion service metadata with clearnet traces, timing attacks, correlation of writing style and PGP keys — used both by law enforcement hunting criminals and by threat actors hunting journalists and dissidents. |
| Criminal automation | Autonomous agents placing orders, posting ads, messaging vendors, managing mule accounts, draining wallets — an entire criminal operation running without a human ever in the loop. |
| Disinformation infrastructure | Coordinated persona networks on hidden boards, fabricated document drops timed to bleed into legitimate OSINT pipelines, synthetic intelligence that reads real but originates from nowhere. |
| Zero-day brokerage | Automated monitoring of exploit vendor channels, private CVE auction boards, and vulnerability markets — buy-side and sell-side intelligence gathered faster than any human analyst. |
The 2026 internet is already at the edge of this. Within five years, AI agents that can: