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 Qingyon-AI · MCP Server · ★ 292
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Revornix safe to install? View the security audit →
English 日本語ドキュメント Reject FOMO! When facing the information stream, be lazy, leave the rest to AI! Revornix is an open-source, local-first AI information workspace. Save the noisy stream of links, papers, audio and screenshots you can't keep up with, and let the platform turn them into structured knowledge, generate reports and podcasts you can actually consume, and deliver the result through notifications when you're ready. The whole stack — web client, gateway, API, async workers, trending feed, docs site — is open and self-hostable. Links Official site: Live workspace: <https://app.revornix.com
| Stars | 292 |
| Forks | 37 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 64.5322287352084/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-22 |
| Created | 2025-04-06 |
| Platforms | mcp, node |
| Est. Tokens | ~16k |
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Revornix is Revornix is an open-source, local-first AI information/markdown workspace. It helps you collect fragmented inputs, turn them into structured knowledge, generate reports with images and podcast audio, . It is categorized as a MCP Server with 292 GitHub stars.
Revornix is primarily written in TypeScript. It covers topics such as agent, ai, markdown.
You can find installation instructions and usage details in the Revornix GitHub repository at github.com/Qingyon-AI/Revornix. The project has 292 stars and 37 forks, indicating an active community.
The top alternatives to Revornix on Agent Skills Hub include flock, argo, aser. 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: