Anything-to-NotebookLM
Integrates with Google NotebookLM to transform multi-source content into AI-generated formats like podcasts, presentations, mind maps, and quizzes.
Utilizes OCR to extract text from JPEG images, allowing them to be processed and converted into structured documents.
Supports Markdown files as input sources and generates output reports and summaries in Markdown format.
Allows for the ingestion of XML-based structured data for conversion into reports and other AI-generated formats.
Extracts transcripts from YouTube videos to be used as content sources for automated analysis and conversion into structured documents.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Anything-to-NotebookLMTurn this YouTube video into a podcast: https://youtube.com/watch?v=abc"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🎯 Anything → NotebookLM
Multi-source Content Intelligent Processor: Anything → Podcast / PPT / Mind Map / Quiz
Quick Start • Supported Formats • Usage Examples • Paywall Bypass • FAQ
✨ What is this?
A Claude Code Skill that turns anything into any format using natural language.
你说:把这篇微信文章生成播客
AI :✅ 8 分钟播客已生成 → podcast.mp3
你说:这个付费文章做成思维导图
AI :✅ 自动绕过付费墙 → 思维导图已生成
你说:这期播客(小宇宙)做成 PPT
AI :✅ 自动转录音频 → 25 页 PPT 已生成Core Capabilities: Multi-source content acquisition (including paywall bypass) → Upload to Google NotebookLM → AI-generated target format.
Related MCP server: KHU Notebook Research Assistant
🚀 Supported Content Sources (15+)
📱 Social & Media
WeChat Official Accounts (MCP browser simulation)
X/Twitter (Tweets + long threads)
YouTube Videos (Automatic subtitle extraction)
Podcasts (Xiaoyuzhou / Ximalaya / Bilibili)
🌐 Web (Including Paywall Bypass)
300+ Paywalled Sites (NYT/WSJ/FT/Economist...)
Any Public Webpage (News, blogs, documents)
Search Keywords (Automatic result aggregation)
📚 E-books & Documents
PDF (Supports OCR for scanned copies)
EPUB E-books
Markdown (.md)
Plain Text (.txt)
📄 Office Documents
Word (.docx)
PowerPoint (.pptx)
Excel (.xlsx)
🖼️ Others
Images (JPEG/PNG, automatic OCR)
Audio (WAV/MP3, automatic transcription)
ZIP Archives (Batch processing)
🛡️ Paywall Bypass
Core Feature: Automatically detects and bypasses paywalls for 300+ news websites.
Bypass Strategy (6-Layer Cascade)
Level 1: 代理服务(r.jina.ai / defuddle.md)
↓ 失败
Level 2: 站点专属 Bot UA(Googlebot ~50站 / Bingbot ~4站)
↓ 失败
Level 3: 通用绕过(UA伪装 + X-Forwarded-For + Referer伪装 + AMP + EU IP)
↓ 失败
Level 4: archive.today 存档(CAPTCHA 自动检测)
↓ 失败
Level 5: Google Cache
↓ 失败
Level 6: agent-fetch 本地工具Supported Paywalled Sites (Partial)
Category | Sites |
🇺🇸 US Media | NYT, WSJ, Bloomberg, Washington Post, The Information, Forbes, WIRED, The New Yorker, The Atlantic, USA Today, Boston Globe, LA Times, Chicago Tribune, Seattle Times, MIT Tech Review, Foreign Affairs |
🇬🇧 UK Media | FT, The Times, The Telegraph, The Economist |
🇩🇪 German Media | Spiegel, Zeit, Sueddeutsche, FAZ, Handelsblatt |
🇫🇷 French Media | Le Monde, Le Figaro, Le Parisien |
🇦🇺 Australian Media | The Australian, SMH, The Age, Brisbane Times |
🇨🇳 Chinese Media | SCMP, Medium |
🌐 Others | Haaretz, NZ Herald, Statista, Quora |
Bypass Technology (Learned from Bypass Paywalls Clean)
Technology | Principle | Coverage |
Googlebot UA + X-Forwarded-For | Search engine crawler whitelist, direct full-text access | ~50 sites |
Bingbot UA | Same as above, some sites are more friendly to Bing | ~4 sites |
Cookie Clearing + Referer Spoofing | Clear metered cookies, spoof origin from Google/Facebook/Twitter | Metered paywalls |
AMP Pages | AMP versions have weaker paywall implementations | ~10 sites |
JSON-LD Extraction | Extract articleBody from HTML-embedded structured data | Universal |
archive.today | Retrieve saved content from web archives | Fallback solution |
🎨 What can be generated?
Output Format | Purpose | Trigger Word Examples |
🎙️ Podcast | Listen during commute | "Generate podcast", "Make into audio" |
📊 PPT | Team sharing | "Make into PPT", "Generate slides" |
🗺️ Mind Map | Clarify structure | "Draw a mind map", "Generate mind map" |
📝 Quiz | Self-assessment | "Generate Quiz", "Create questions" |
🎬 Video | Visualization | "Make a video" |
📄 Report | Deep analysis | "Generate report", "Write a summary" |
📈 Infographic | Data visualization | "Make an infographic" |
📋 Flashcards | Memory consolidation | "Make into flashcards" |
⚡ Quick Start
Prerequisites
✅ Python 3.9+
✅ Git (Pre-installed on macOS/Linux)
That's it! Other dependencies are installed automatically with one click.
Installation (3 Steps)
# 1. 克隆到 Claude skills 目录
cd ~/.claude/skills/
git clone https://github.com/joeseesun/qiaomu-anything-to-notebooklm
cd qiaomu-anything-to-notebooklm
# 2. 一键安装所有依赖
./install.sh
# 3. 按提示配置 MCP,然后重启 Claude CodeFirst Use
# NotebookLM 认证(只需一次)
notebooklm login
notebooklm list # 验证成功
# 环境检查(可选)
./check_env.pyPodcast Transcription Configuration (Optional)
To use the Xiaoyuzhou/Ximalaya/Bilibili transcription feature, configure the GetNote API:
export GETNOTE_API_KEY="your_api_key"
export GETNOTE_CLIENT_ID="your_client_id"💡 Usage Examples
Scenario 1: Paywalled Article → Podcast
你:把这篇 The Information 文章生成播客 https://www.theinformation.com/articles/...
AI 自动执行:
✓ 检测付费墙 → Googlebot UA 绕过
✓ 获取完整文章内容
✓ 上传到 NotebookLM
✓ 生成播客
✅ 结果:/tmp/article_podcast.mp3Scenario 2: Podcast (Xiaoyuzhou) → PPT
你:这期小宇宙播客做成 PPT https://xiaoyuzhoufm.com/episode/...
AI 自动执行:
✓ Get笔记 API 转写音频(2-5 分钟)
✓ 上传转写文本到 NotebookLM
✓ 生成 PPT
✅ 结果:/tmp/podcast_slides.pdf(25 页)Scenario 3: E-book → Deep Analysis
你:深度分析这本书 /Users/joe/Books/sapiens.epub
AI 自动执行:
✓ 提取 EPUB 全文
✓ 上传到 NotebookLM
✓ 生成 12 个问题(3 轮递进:概览→深度挖掘→综合反刍)
✓ 逐轮提问,后轮受益于前轮对话上下文
✓ 输出结构化 JSON
✅ 结果:/tmp/sapiens_analysis.json(12 个问答,含核心观点、论证拆解、矛盾分析、认知改变)Scenario 4: X/Twitter Thread → Mind Map
你:这个推文线程做成思维导图 https://x.com/user/status/123...
AI 自动执行:
✓ 代理级联获取推文内容(含完整线程)
✓ 上传到 NotebookLM
✓ 生成思维导图
✅ 结果:/tmp/tweet_mindmap.jsonScenario 5: WeChat Article → Lark/Feishu Doc (Deep Analysis)
你:深度分析这篇微信文章并写入飞书 https://mp.weixin.qq.com/s/abc123
AI 自动执行:
✓ MCP 浏览器模拟抓取微信文章
✓ 上传到 NotebookLM
✓ 生成 10 个问题并递归提问
✓ 格式化为飞书 Markdown
✓ 自动创建飞书文档
✅ 结果:飞书文档已创建(含完整问答)🎯 Core Features
🧠 Intelligent Recognition
Automatically determines input type, no manual specification needed.
https://mp.weixin.qq.com/s/xxx → 微信公众号
https://xiaoyuzhoufm.com/episode/xxx → 小宇宙播客
https://x.com/user/status/xxx → X/Twitter
https://youtube.com/watch?v=xxx → YouTube 视频
/path/to/file.epub → EPUB 电子书
"搜索 'AI 趋势'" → 搜索查询🛡️ Automatic Paywall Bypass
No manual handling required, automatically detected and bypassed.
检测付费墙 → 选择最佳策略 → 获取完整内容
︿________全自动________︿🚀 Fully Automated Processing
From acquisition to generation, all in one go.
输入 → 获取 → 转换 → 上传 → 生成 → 下载
︿___________全自动___________︿🌐 Multi-source Integration
Supports mixing multiple content sources.
付费文章 + YouTube 视频 + EPUB + 播客 → 综合报告📦 Technical Architecture
┌──────────────────────────────────────────┐
│ 用户自然语言输入 │
│ "把这个付费文章生成播客 https://..." │
└──────────────────┬───────────────────────┘
│
▼
┌──────────────────────────────────────────┐
│ Claude Code Skill │
│ • 智能识别内容源类型 │
│ • 自动调用对应工具 │
└──────────┬───────────────────────────────┘
│
┌───────┴───────┐
│ │
▼ ▼
┌──────────┐ ┌──────────────┐ ┌──────────┐ ┌──────────┐
│ 微信 MCP │ │ 付费墙绕过 │ │ 播客转写 │ │ markitdown│
│ 浏览器模拟 │ │ 6层级联策略 │ │ Get笔记API│ │ 文件转换 │
└─────┬────┘ └──────┬───────┘ └─────┬────┘ └─────┬────┘
│ │ │ │
└──────────────┴─────────────────┴──────────────┘
│
▼
┌────────────────────────┐
│ NotebookLM API │
│ • 上传内容源 │
│ • AI 生成目标格式 │
└───────────┬────────────┘
│
▼
┌────────────────────────┐
│ 生成的文件 │
│ .mp3 / .pdf / .json │
└────────────────────────┘📂 Project Structure
qiaomu-anything-to-notebooklm/
├── SKILL.md # Skill 定义文件
├── README.md # 本文件
├── main.py # 主入口:CLI 智能处理器
├── install.sh # 一键安装脚本
├── check_env.py # 13 项环境检查
├── package.sh # 打包分享脚本
├── requirements.txt # Python 依赖
├── LICENSE # MIT
├── scripts/
│ ├── fetch_url.sh # URL 抓取 + 付费墙绕过(6 层级联)
│ └── get_podcast_transcript.py # 播客/视频转写(Get笔记 API)
├── wexin-read-mcp/ # 微信公众号 MCP 服务器
│ └── src/
│ ├── server.py # MCP 入口
│ ├── scraper.py # Playwright 浏览器模拟
│ └── parser.py # HTML 解析
└── feishu-read-mcp/ # 飞书文档 MCP 服务器
└── src/
├── server.py # MCP 入口
├── scraper.py # 飞书文档抓取
├── parser.py # HTML → Markdown
└── image_handler.py # 图片处理🔧 Advanced Usage
Deep Analysis Mode
python main.py https://example.com/article --deep-analysis
# 自动生成 12 个问题(3 轮递进:概览→深度挖掘→综合反刍),逐轮提问,输出结构化 JSONThree-Round Progressive Strategy:
Round | Number of Questions | Purpose | Examples |
Round 1: Overview & Framework | 4 | Establish overall understanding | Summarize topic, list structure, extract core arguments, uncover disruptive content |
Round 2: Deep Dive | 5 | Explore details | Deconstruct logic, analyze contradictions, distill core insights, propose sharp criticism |
Round 3: Synthesis & Reflection | 3 | Cognitive upgrade | Biggest cognitive shift, action guide, recommendation reasons |
NotebookLM maintains context within the same session; subsequent round questions automatically benefit from previous answers, forming a true "progressive" deep analysis.
Lark/Feishu Doc Output
python main.py ./book.epub --deep-analysis --to-feishu
# 深度分析后自动创建飞书文档Batch Processing
把这些文章都生成播客:
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 chromiumNotebookLM Authentication Failed
notebooklm login # 重新登录
notebooklm list # 验证Paywall Bypass Failed
Some hard-paywall sites (like The Information) do not send content server-side, requiring archive.today. The script will automatically detect and prompt:
⚠️ archive.ph needs human verification.
已自动打开浏览器,请完成验证后重试Environment Check
./check_env.py # 13 项全面检查
./install.sh # 重新安装❓ FAQ
A: NotebookLM supports multiple languages; Chinese and English perform best.
A: Google AI voice synthesis. English is a dialogue between two AI hosts; Chinese is a single-person narration.
A: This tool is for personal study and research only. The technical principle is based on search engine whitelists (Googlebot/Bingbot) and does not crack any encryption. It is recommended to support high-quality news media by purchasing subscriptions.
A:
Minimum: ~500 words
Maximum: ~500,000 words
Recommended: 1,000-10,000 words for best results
A: WeChat Official Accounts have anti-scraping measures; MCP uses Playwright browser simulation to bypass them. Other content sources (webpages, YouTube, PDF) do not require MCP.
A: Supported via GetNote API for Xiaoyuzhou, Ximalaya, and Bilibili videos. YouTube is handled directly by NotebookLM.
🙏 Acknowledgments
Google NotebookLM - AI content generation
Microsoft markitdown - File conversion
Bypass Paywalls Clean - Paywall bypass strategy reference
wexin-read-mcp - WeChat scraping
notebooklm-py - NotebookLM CLI
📄 License
MIT License - For personal study and research use only
If you find this useful, please give it a ⭐ Star!
Made with ❤️ by Joe · Twitter @vista8 · WeChat Official Account "向阳乔木推荐看"
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