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 joeseesun · MCP Server · ★ 6.0k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is qiaomu-anything-to-notebooklm safe to install? View the security audit →
Featured in: Document Parsing
🎯 多源内容 → NotebookLM 智能处理器 一句话变播客、PPT、思维导图、Quiz... 快速开始 • 支持格式 • 使用示例 • 常见问题 ✨ 这是什么？ 一个 Claude Code Skill，让你用自然语言把任何内容变成任何格式。 原理：自动从多种来源获取内容 → 上传到 Google NotebookLM → AI 生成你想要
| Stars | 5,995 |
| Forks | 649 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.9611001403611/100 |
| Open Issues | 6 |
| Last Updated | 2026-04-28 |
| Created | 2026-01-25 |
| Platforms | browser, claude-code, mcp, python |
| Est. Tokens | ~14k |
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qiaomu-anything-to-notebooklm is Claude Skill: Multi-source content processor for NotebookLM. Supports WeChat articles, web pages, YouTube, PDF, Markdown, search queries → Podcast/PPT/MindMap/Quiz etc.. It is categorized as a MCP Server with 6.0k GitHub stars.
qiaomu-anything-to-notebooklm is primarily written in Python. It covers topics such as automation, claude, mcp.
You can find installation instructions and usage details in the qiaomu-anything-to-notebooklm GitHub repository at github.com/joeseesun/qiaomu-anything-to-notebooklm. The project has 6.0k stars and 649 forks, indicating an active community.
qiaomu-anything-to-notebooklm is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to qiaomu-anything-to-notebooklm on Agent Skills Hub include openpencil, gpt-researcher, trigger.dev. 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: