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 Chamanrajragu · MCP Server · ★ 21
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is purffle-shorts safe to install? View the security audit →
Free open-source AI YouTube Shorts generator and faceless video maker in Python. Any LLM (GPT, Claude, Gemini, Ollama) writes scripts; text-to-speech, stock footage or AI images, word-synced captions, text-message chat and Reddit story videos, podcast and long video clipping, YouTube auto-upload and scheduling. TikTok and Reels ready. MCP server.
| Stars | 21 |
| Forks | 3 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 59.2860323758113/100 |
| Last Updated | 2026-09-30 |
| Created | 2026-06-13 |
| Platforms | claude-code, cli, gemini, mcp, python |
| Est. Tokens | ~25k |
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purffle-shorts is Free open-source AI YouTube Shorts generator and faceless video maker in Python. Any LLM (GPT, Claude, Gemini, Ollama) writes scripts; text-to-speech, stock footage or AI images, word-synced captions,. It is categorized as a MCP Server with 21 GitHub stars.
purffle-shorts is primarily written in Python. It covers topics such as ai-video-generator, faceless, faceless-video.
You can find installation instructions and usage details in the purffle-shorts GitHub repository at github.com/Chamanrajragu/purffle-shorts. The project has 21 stars and 3 forks, indicating an active community.
purffle-shorts is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to purffle-shorts on Agent Skills Hub include HappyHorse-1.0-API, podcli, mcp-video. 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: