Someone used Claude to build a content nuke, and I can’t in good conscience not mention it. Throw anything at it—WeChat articles, YouTube, podcasts, PDFs, Word, Excel, ebooks—and it spits out podcasts, PPTs, mind maps. The most outrageous part? 300+ paid sites like NYT, FT, The Economist—paywalls are treated like air. All natural language, no code needed. If you’re a learner, content creator, or knowledge manager, not bookmarking this is a loss. https://github.com/joeseesun/qiaomu-anything-to-notebooklm…

joeseesun/qiaomu-anything-to-notebooklm

Source: https://github.com/joeseesun/qiaomu-anything-to-notebooklm

🎯 Anything → NotebookLM

Multi-source content smart processor: any content → podcast / PPT / mind map / Quiz

License: MIT (https://opensource.org/licenses/MIT)
Python 3.9+ (https://www.python.org/downloads/)
PRs Welcome (http://makeapullrequest.com)
GitHub stars (https://github.com/joeseesun/qiaomu-anything-to-notebooklm/stargazers)
GitHub forks (https://github.com/joeseesun/qiaomu-anything-to-notebooklm/network/members)
GitHub issues (https://github.com/joeseesun/qiaomu-anything-to-notebooklm/issues)
GitHub last commit (https://github.com/joeseesun/qiaomu-anything-to-notebooklm/commits/main)

Quick Start • Supported Formats • Usage Examples • Paywall Bypass • FAQ

✨ What is this?

A Claude Code Skill that turns any content into any format using natural language.

You say: Turn this WeChat article into a podcast  
AI: ✅ 8-minute podcast generated → podcast.mp3  

You say: Make this paywalled article into a mind map  
AI: ✅ Auto-bypassed paywall → mind map generated  

You say: Turn this podcast (Xiaoyuzhou) into a PPT  
AI: ✅ Auto transcribed audio → 25-page PPT generated  

Core capability: Multi-source content acquisition (including paywall bypass) → upload to Google NotebookLM (https://notebooklm.google.com/) → AI generates target format

🚀 Supported Content Sources (15+)

📱 Social & Media

• WeChat Official Accounts (MCP browser simulation)
• X/Twitter (tweets + long threads)
• YouTube videos (auto subtitle extraction)
• Podcasts (Xiaoyuzhou / Ximalaya / Bilibili)

🌐 Web Pages (including paywall bypass)

• 300+ paywalled sites (NYT/WSJ/FT/Economist…)
• Any public webpage (news, blogs, docs)
• Search keywords (auto aggregated results)

📚 Ebooks & Documents

• PDF (supports scanned OCR)
• EPUB ebooks
• Markdown (.md)
• Plain text (.txt)

📄 Office Documents

• Word (.docx)
• PowerPoint (.pptx)
• Excel (.xlsx)

🖼️ Other

• Images (JPEG/PNG, auto OCR)
• Audio (WAV/MP3, auto transcription)
• ZIP archives (batch processing)

🛡️ Paywall Bypass

Core feature: Automatically detects and bypasses paywalls on 300+ paid news sites.

Bypass Strategies (6-level cascade)

Level 1: Proxy service (r.jina.ai / defuddle.md)  
↓ if fails  
Level 2: Site-specific Bot UA (Googlebot ~50 sites / Bingbot ~4 sites)  
↓ if fails  
Level 3: Generic bypass (UA spoof + X-Forwarded-For + Referer spoof + AMP + EU IP)  
↓ if fails  
Level 4: archive.today snapshot (CAPTCHA auto detection)  
↓ if fails  
Level 5: Google Cache  
↓ if fails  
Level 6: agent-fetch local tool  

Supported Paywalled Sites (Partial)

Bypass Techniques (Learned from Bypass Paywalls Clean (https://gitflic.ru/project/magnolia1234/bypass-paywalls-chrome-clean))

🎨 What Can Be Generated?

⚡ Quick Start

Prerequisites

• ✅ Python 3.9+
• ✅ Git (built-in on macOS/Linux)

That’s all! Other dependencies installed automatically with one click.

Installation (3 steps)

# 1. Clone into Claude skills directory  
cd ~/.claude/skills/  
git clone https://github.com/joeseesun/qiaomu-anything-to-notebooklm  
cd qiaomu-anything-to-notebooklm  

# 2. One-click install all dependencies  
./install.sh  

# 3. Configure MCP as prompted, then restart Claude Code  

First Use

# NotebookLM authentication (only once)  
notebooklm login  
notebooklm list  # verify success  

# Environment check (optional)  
./check_env.py  

Podcast Transcription Configuration (Optional)

To use Xiaoyuzhou / Ximalaya / Bilibili transcription, configure Get笔记 API:

export GETNOTE_API_KEY="your_api_key"  
export GETNOTE_CLIENT_ID="your_client_id"  

💡 Usage Examples

Scenario 1: Paywalled Article → Podcast

You: Turn this The Information article into a podcast  
https://www.theinformation.com/articles/...  

AI auto-executes:  
✓ Detects paywall → Googlebot UA bypass  
✓ Fetches full article content  
✓ Uploads to NotebookLM  
✓ Generates podcast  
✅ Result: /tmp/article_podcast.mp3  

Scenario 2: Podcast (Xiaoyuzhou) → PPT

You: Turn this Xiaoyuzhou podcast into a PPT  
https://xiaoyuzhoufm.com/episode/...  

AI auto-executes:  
✓ Get笔记 API transcribes audio (2-5 min)  
✓ Uploads transcription to NotebookLM  
✓ Generates PPT  
✅ Result: /tmp/podcast_slides.pdf (25 pages)  

Scenario 3: Ebook → Deep Analysis

You: Deep analyze this book /Users/joe/Books/sapiens.epub  

AI auto-executes:  
✓ Extracts full EPUB text  
✓ Uploads to NotebookLM  
✓ Generates 12 questions (3 progressive rounds: overview → deep dive → synthesis)  
✓ Asks round by round, later rounds benefit from prior dialog context  
✓ Outputs structured JSON  
✅ Result: /tmp/sapiens_analysis.json (12 Q&A with core ideas, argument breakdown, contradiction analysis, cognitive shifts)  

Scenario 4: X/Twitter Thread → Mind Map

You: Make this tweet thread into a mind map  
https://x.com/user/status/123...  

AI auto-executes:  
✓ Proxy cascade fetches tweet content (full thread)  
✓ Uploads to NotebookLM  
✓ Generates mind map  
✅ Result: /tmp/tweet_mindmap.json  

Scenario 5: WeChat Article → Feishu Document (Deep Analysis)

You: Deep analyze this WeChat article and write to Feishu  
https://mp.weixin.qq.com/s/abc123  

AI auto-executes:  
✓ MCP browser simulation grabs WeChat article  
✓ Uploads to NotebookLM  
✓ Generates 10 questions and asks recursively  
✓ Formats as Feishu Markdown  
✓ Auto-creates Feishu document  
✅ Result: Feishu document created (full Q&A included)  

🎯 Core Features

🧠 Smart Recognition

Auto detects input type, no manual specification needed

https://mp.weixin.qq.com/s/xxx → WeChat Official Account  
https://xiaoyuzhoufm.com/episode/xxx → Xiaoyuzhou Podcast  
https://x.com/user/status/xxx → X/Twitter  
https://youtube.com/watch?v=xxx → YouTube Video  
/path/to/file.epub → EPUB ebook  
"search 'AI trends'" → Search query  

🛡️ Automatic Paywall Bypass

No manual handling needed, auto detects and bypasses

Detect paywall → Select best strategy → Get full content  
〈________fully automatic________〈  

🚀 Fully Automated Processing

From acquisition to generation, all in one go

Input → Fetch → Convert → Upload → Generate → Download  
〈___________fully automatic___________〈  

🌐 Multi-Source Integration

Supports mixing multiple content sources

Paywalled article + YouTube video + EPUB + podcast → comprehensive report  

📦 Technical Architecture

┌──────────────────────────────────────────┐  
│ User natural language input              │  
│ "Turn this paywalled article into podcast │  
│  https://..."                            │  
└──────────────────┬───────────────────────┘  
                   │  
                   ▼  
┌──────────────────────────────────────────┐  
│ Claude Code Skill                        │  
│ • Smart recognizes content source type   │  
│ • Auto invokes corresponding tools       │  
└──────────┬───────────────────────────────┘  
           │  
    ┌──────┴──────┐  
    │             │  
    ▼             ▼  
┌──────────┐ ┌──────────────┐ ┌──────────┐ ┌──────────┐  
│ WeChat   │ │ Paywall      │ │ Podcast  │ │markitdown│  
│ MCP      │ │ Bypass       │ │Transcript│ │ File     │  
│ Browser  │ │ 6-level      │ │ Get笔记  │ │ Convert  │  
│ Simulate │ │ Cascade      │ │ API      │ │          │  
└─────┬────┘ └──────┬───────┘ └─────┬────┘ └─────┬────┘  
      │             │               │            │  
      └─────────────┴───────────────┴────────────┘  
                        │  
                        ▼  
            ┌────────────────────────┐  
            │ NotebookLM API          │  
            │ • Upload content source │  
            │ • AI generate target    │  
            │   format                │  
            └───────────┬────────────┘  
                        │  
                        ▼  
            ┌────────────────────────┐  
            │ Generated files        │  
            │ .mp3 / .pdf / .json    │  
            └────────────────────────┘  

📂 Project Structure

qiaomu-anything-to-notebooklm/  
├── SKILL.md               # Skill definition file  
├── README.md              # This file  
├── main.py                # Main entry: CLI smart processor  
├── install.sh             # One-click install script  
├── check_env.py           # 13-item environment check  
├── package.sh             # Package & share script  
├── requirements.txt       # Python dependencies  
├── LICENSE                # MIT  
├── scripts/  
│   ├── fetch_url.sh       # URL fetch + paywall bypass (6-level cascade)  
│   └── get_podcast_transcript.py  # Podcast/video transcription (Get笔记 API)  
├── wexin-read-mcp/        # WeChat Official Account MCP server  
│   └── src/  
│       ├── server.py      # MCP entry  
│       ├── scraper.py     # Playwright browser simulation  
│       └── parser.py      # HTML parsing  
└── feishu-read-mcp/       # Feishu Document MCP server  
    └── src/  
        ├── server.py      # MCP entry  
        ├── scraper.py     # Feishu document fetch  
        ├── parser.py      # HTML → Markdown  
        └── image_handler.py  # Image processing  

🔧 Advanced Usage

Deep Analysis Mode

python main.py https://example.com/article --deep-analysis  
# Auto generates 12 questions (3 progressive rounds: overview → deep dive → synthesis), asks round by round, outputs structured JSON  

Three-round progressive strategy:

NotebookLM maintains context within the same session; later round questions automatically benefit from earlier answers, enabling true “progressive” deep analysis.

Feishu Document Output

python main.py ./book.epub --deep-analysis --to-feishu  
# After deep analysis, auto-creates Feishu document  

Batch Processing

Turn these articles into podcasts:  
1. https://mp.weixin.qq.com/s/abc123  
2. https://www.wsj.com/articles/...  
3. /Users/joe/notes.md  

🐛 Troubleshooting

MCP Tool Not Found

python ~/.claude/skills/qiaomu-anything-to-notebooklm/wexin-read-mcp/src/server.py  
cd ~/.claude/skills/qiaomu-anything-to-notebooklm/wexin-read-mcp  
pip install -r requirements.txt  
playwright install chromium  

NotebookLM Authentication Failed

notebooklm login   # Re-login  
notebooklm list    # Verify  

Paywall Bypass Failed

Some hard paywall sites (e.g., The Information) don’t send content server-side; an archive.today snapshot is needed. The script will auto-detect and prompt:

⚠️ archive.ph needs human verification.  
Browser opened automatically. Please complete verification and retry.  

Environment Check

./check_env.py   # 13-item comprehensive check  
./install.sh     # Reinstall  

❓ FAQ

Q: What languages are supported?
A: NotebookLM supports multiple languages; Chinese and English work best.

Q: Who voices the podcasts?
A: Google AI speech synthesis. English features two AI hosts in conversation; Chinese is a single narrator.

Q: Is paywall bypass legal?
A: This tool is for personal study and research only. The technology is based on search engine whitelisting (Googlebot/Bingbot) and does not crack any encryption. Supporting quality news media by purchasing subscriptions is recommended.

Q: Content length limits?
A:

• Minimum: ~500 characters
• Maximum: ~500,000 characters
• Recommended: 1,000–10,000 characters for best results

Q: Why is MCP needed?
A: WeChat Official Accounts have anti-scraping measures; MCP uses Playwright browser simulation to bypass. Other content sources (web pages, YouTube, PDFs) don’t require MCP.

Q: Which platforms does podcast transcription support?
A: Through the Get笔记 API, it supports Xiaoyuzhou, Ximalaya, and Bilibili videos. YouTube is handled directly by NotebookLM.

🙏 Acknowledgements

• Google NotebookLM (https://notebooklm.google.com/) – AI content generation
• Microsoft markitdown (https://github.com/microsoft/markitdown) – File conversion
• Bypass Paywalls Clean (https://gitflic.ru/project/magnolia1234/bypass-paywalls-chrome-clean) – Paywall bypass strategy reference
• wexin-read-mcp (https://github.com/Bwkyd/wexin-read-mcp) – WeChat scraping
• notebooklm-py (https://github.com/teng-lin/notebooklm-py) – NotebookLM CLI

📄 License

MIT License – For personal study and research use only

If you find this useful, please give a ⭐ Star!

Made with ❤️ by Joe (https://github.com/joeseesun) · Twitter @vista8 (https://x.com/vista8) · WeChat Official Account「向阳乔木推荐看」