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 0xchamin · MCP Server · ★ 148
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcptube safe to install? View the security audit →
🎬 mcptube-vision YouTube video knowledge engine — transcripts, vision, and persistent wiki. mcptube-vision transforms YouTube videos into a persistent, structured knowledge base using both transcripts and visual frame analysis. Built on the Karpathy LLM Wiki pattern: knowledge compounds with every video you add. Evolved from mcptube v0.1 — mcptube-vision replaces semantic chunk search with a persistent wiki that gets smarter with every video ingested. 🧠 How It Works Traditional video tools re-discover knowledge from scratch on every query. mcptube-vision is different: mcptube v0.1 mcptube-vision ┌─────────────────────┐ ┌─────────────────────────┐ │ Query → vector search│ │ Video ingested → LLM │ │ → raw chunks → LLM │ │ extracts knowledge → │ │ → answer (from scratch│ │ wiki pages created → │ │ every time) │ │ cross-references built │ └─────────────────────┘ │ │ │ Query → FTS5
| Stars | 148 |
| Forks | 13 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 55.7079444476696/100 |
| Open Issues | 4 |
| Last Updated | 2026-04-13 |
| Created | 2026-02-28 |
| Platforms | claude-code, codex, gemini, mcp, python |
| Est. Tokens | ~101k |
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mcptube is an open-source mcp server by 0xchamin with 148 GitHub stars.
mcptube is primarily written in Python. It covers topics such as ai, claude, codex.
You can find installation instructions and usage details in the mcptube GitHub repository at github.com/0xchamin/mcptube. The project has 148 stars and 13 forks, indicating an active community.
The top alternatives to mcptube on Agent Skills Hub include Overture, yutu, ClaudeR. 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: