notebooklm-skill

NotebookLM does the research, Claude writes the content.

The only tool that connects trending topic discovery → NotebookLM deep research → AI content creation → multi-platform publishing. Works as a Claude Code Skill or standalone MCP Server.

繁體中文版 README

Demo

Language	YouTube	Slides
English	Watch	6 pages, auto-generated
繁體中文	Watch	5 pages, auto-generated

All slides, podcasts, and videos were generated by NotebookLM using this tool.

What is this?

notebooklm-skill bridges NotebookLM's research capabilities with Claude's content generation. Feed it URLs, PDFs, or trending topics — it creates a NotebookLM notebook, runs deep research queries, and hands structured findings to Claude for polished output: articles, social posts, newsletters, podcasts, or any format you need.

Built on notebooklm-py v0.3.4 — pure async Python, no OAuth setup needed.

Sources (URLs, PDFs)          NotebookLM                Claude               Artifacts & Platforms
+-----------------+    +------------------+    +-----------------+    +----------------------+
| Web articles    |--->| Create notebook  |--->| Draft article   |--->| Blog / CMS           |
| Research papers |    | Add sources      |    | Social posts    |    | Threads / X          |
| YouTube videos  |    | Ask questions    |    | Newsletter      |    | Newsletter           |
| Trending topics |    | Extract insights |    | Any format      |    | Any platform         |
+-----------------+    +------------------+    +-----------------+    +----------------------+
     Phase 1                Phase 2                Phase 3                  Phase 4
                                |
                                v
                       +------------------+
                       | Generate artifacts|
                       | Audio (podcast)   |
                       | Video             |
                       | Slides            |
                       | Report            |
                       | Quiz              |
                       | Flashcards        |
                       | Mind map          |
                       | Infographic       |
                       | Data table        |
                       | Study guide       |
                       +------------------+
                            Phase 2b

Quick Start

# 1. Install
git clone https://github.com/claude-world/notebooklm-skill.git
cd notebooklm-skill
pip install -r requirements.txt   # installs notebooklm-py v0.3.4

# 2. Authenticate with Google (one-time, opens browser)
python3 -m notebooklm login
# -> Opens Chromium, sign in to Google
# -> Session saved to ~/.notebooklm/storage_state.json
# -> All subsequent calls use pure HTTP (no browser needed)

# 3. Create your first notebook
python scripts/notebooklm_client.py create \
  --title "My Research" \
  --sources https://example.com/article

# 4. Ask research questions
python scripts/notebooklm_client.py ask \
  --notebook "My Research" \
  --query "What are the key findings?"

# 5. Generate a podcast
python scripts/notebooklm_client.py podcast \
  --notebook "My Research" \
  --lang en \
  --output podcast.m4a

# 6. Verify auth status
python scripts/auth_helper.py verify

See docs/SETUP.md for the full setup guide.

Authentication

notebooklm-py uses browser-based Google login (no OAuth Client ID needed):

Step	Command	What happens
Login	`python3 -m notebooklm login`	Opens Chromium, user logs into Google
Session storage	Automatic	Saved to `~/.notebooklm/storage_state.json`
Subsequent use	`NotebookLMClient.from_storage()`	Reads saved session, pure HTTP calls
Verify	`python scripts/auth_helper.py verify`	Loads client + calls `notebooks.list()`
Clear	`python scripts/auth_helper.py clear`	Removes `~/.notebooklm/` directory

Session typically lasts weeks. Re-run login if you get authentication errors.

Two Ways to Use

	Claude Code Skill	MCP Server
Best for	Claude Code users who want NotebookLM in their workflow	Any MCP-compatible client (Cursor, Gemini CLI, etc.)
Setup	Copy skill to `.claude/skills/`	Add server to MCP config
Invocation	Claude auto-detects when relevant	Tools appear in client tool list
Config	`SKILL.md` + `.env`	`mcp.json` + `.env`
Requirements	Python 3.10+, notebooklm-py	Python 3.10+, notebooklm-py

Features

Feature	Description	Status
Notebook CRUD	Create, list, delete notebooks	Available
Source ingestion	Add URLs, PDFs, YouTube links, plain text	Available
Research queries	Ask questions against notebook sources with citations	Available
Structured extraction	Get key facts, arguments, timelines	Available
Content generation	Use research output as context for Claude	Available
Batch operations	Process multiple sources or queries at once	Available
trend-pulse integration	Auto-discover trending topics to research	Available
threads-viral-agent integration	Publish research-backed social posts	Available

Artifact Generation (10 types)

Artifact	Format	Description
Audio	M4A	AI-generated podcast discussion
Video	MP4	Video summary with visuals
Slides	PDF	Presentation deck
Report	PDF	Comprehensive written report
Quiz	JSON	Multiple-choice assessment questions
Flashcards	JSON	Study flashcard deck
Mind map	SVG	Visual concept map
Infographic	PNG	Visual data summary
Data table	CSV	Structured data extraction
Study guide	PDF	Structured learning material

All artifacts support language selection (e.g., --lang zh-TW).

Note: NotebookLM returns audio in MPEG-4 (M4A) format, not MP3.

Architecture

+---------------------------------------------------------------+
|                      notebooklm-skill                          |
|                                                                |
|  +---------+  +--------------+  +----------+  +------------+  |
|  | Phase 1 |  |   Phase 2    |  |  Phase 3 |  |  Phase 4   |  |
|  | Collect  |->|  Research    |->| Generate  |->|  Publish   |  |
|  +---------+  +--------------+  +----------+  +------------+  |
|      |              |                |               |         |
|  +--------+  +-------------+  +-----------+  +-----------+    |
|  | URLs   |  | NotebookLM  |  |  Claude    |  | Threads   |    |
|  | PDFs   |  | (via        |  |  Content   |  | Blog      |    |
|  | RSS    |  |  notebooklm |  |  Engine    |  | Email     |    |
|  | Trends |  |  -py 0.3.4) |  |            |  | CMS       |    |
|  +--------+  | - notebooks |  +-----------+  +-----------+    |
|              | - sources   |        |                          |
|              | - chat/ask  |  +-----------+                    |
|              | - artifacts |  | Artifacts |                    |
|              +-------------+  | audio     |                    |
|                               | video     |                    |
|                               | slides    |                    |
|                               | report    |                    |
|                               | quiz      |                    |
|                               | flashcards|                    |
|                               | mind-map  |                    |
|                               | infographic|                   |
|                               | data-table|                    |
|                               | study-guide|                   |
|                               +-----------+                    |
|                                                                |
|  +-----------------------------------------------------------+ |
|  |  Interfaces                                                | |
|  |  +-- scripts/          CLI tools (notebooklm-py direct)   | |
|  |  +-- mcp-server/       MCP protocol server                | |
|  |  +-- SKILL.md          Claude Code skill definition        | |
|  +-----------------------------------------------------------+ |
+---------------------------------------------------------------+
         ^                                          ^
         |                                          |
   +-----------+                             +-----------+
   |trend-pulse|                             |threads-   |
   |(optional) |                             |viral-agent|
   +-----------+                             |(optional) |
                                             +-----------+

Usage Examples

1. Research to Article

python scripts/pipeline.py research-to-article \
  --sources "https://arxiv.org/abs/2401.00001" \
            "https://blog.example.com/ai-agents" \
  --title "AI Agent Survey"

2. Research to Social Posts

python scripts/pipeline.py research-to-social \
  --sources "https://example.com/ai-news" \
  --platform threads \
  --title "AI News This Week"

3. Trending Topics to Content

python scripts/pipeline.py trend-to-content \
  --geo TW \
  --count 5 \
  --platform threads

4. RSS Batch Digest

python scripts/pipeline.py batch-digest \
  --rss "https://example.com/feed.xml" \
  --title "Weekly AI Digest"

5. Generate All Artifacts

python scripts/pipeline.py generate-all \
  --sources "https://example.com/article" \
  --title "Research" \
  --output-dir ./output \
  --language zh-TW

6. Slides + Podcast → YouTube Video

Combine NotebookLM-generated slides and podcast into a YouTube-ready video:

# Generate slides and podcast
python scripts/notebooklm_client.py generate --notebook "Research" --type slides
python scripts/notebooklm_client.py podcast --notebook "Research" --lang en --output podcast.m4a
python scripts/notebooklm_client.py download --notebook "Research" --type slides --output slides.pdf

# Convert PDF to PNG + compose video
./scripts/make_video.sh slides.pdf podcast.m4a output.mp4

Pipeline Workflows

Workflow	Input	Output	Steps
`research-to-article`	URLs, text	Article draft JSON	Create notebook → 5 research questions → article draft
`research-to-social`	URLs, text	Social post draft	Create notebook → summarize → platform-specific post
`trend-to-content`	Geo, count	Content per trend	Fetch trends → create notebooks → research → draft
`batch-digest`	RSS URL	Newsletter digest	Fetch RSS → create notebook → digest + Q&A
`generate-all`	URLs, text	Audio, video, PDF, etc.	Create notebook → generate all artifacts → download

MCP Server Setup

Add to your project's .mcp.json:

{
  "mcpServers": {
    "notebooklm": {
      "command": "python",
      "args": ["-m", "mcp-server"],
      "cwd": "/path/to/notebooklm-skill"
    }
  }
}

Works with Claude Code, Cursor, Gemini CLI, and any MCP-compatible client.

Claude Code Skill Setup

mkdir -p .claude/skills/notebooklm
cp /path/to/notebooklm-skill/SKILL.md .claude/skills/notebooklm/
cp /path/to/notebooklm-skill/scripts/*.py .claude/skills/notebooklm/scripts/
cp /path/to/notebooklm-skill/requirements.txt .claude/skills/notebooklm/

# Authenticate (one-time)
python3 -m notebooklm login

Claude will automatically detect the skill when you ask about research, NotebookLM, or content creation.

API Reference

CLI Commands (11)

Command	Description
`create`	Create a notebook with URL/text sources
`list`	List all notebooks
`delete`	Delete a notebook
`add-source`	Add a source (URL, text, or file) to existing notebook
`ask`	Ask a research question (returns answer + citations)
`summarize`	Get notebook summary
`generate`	Generate an artifact (audio, video, slides, etc.)
`download`	Download a generated artifact
`research`	Run deep web research
`podcast`	Shortcut for `generate --type audio` (auto-downloads)
`qa`	Shortcut for `generate --type quiz`

MCP Tools (13)

Tool	Description
`nlm_create_notebook`	Create notebook with sources
`nlm_list`	List all notebooks
`nlm_delete`	Delete a notebook
`nlm_add_source`	Add source to existing notebook
`nlm_ask`	Ask question (returns answer + citations)
`nlm_summarize`	Get notebook summary
`nlm_generate`	Generate artifact (10 types)
`nlm_download`	Download generated artifact
`nlm_list_sources`	List sources in notebook
`nlm_list_artifacts`	List generated artifacts
`nlm_research`	Deep web research
`nlm_research_pipeline`	Full research pipeline
`nlm_trend_research`	Trend → research pipeline

Integrations

trend-pulse — Real-time trending topic discovery from 7 sources
threads-viral-agent — Auto-publish research-backed social posts

Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes
Push and open a Pull Request

# Development setup
git clone https://github.com/claude-world/notebooklm-skill.git
cd notebooklm-skill
pip install -r requirements.txt
python3 -m notebooklm login
python -m pytest tests/

License

MIT License. See LICENSE.

notebooklm-skill

notebooklm-skill

Demo

What is this?

Quick Start

Authentication

Two Ways to Use

Features

Artifact Generation (10 types)

Architecture

Usage Examples

1. Research to Article

2. Research to Social Posts

3. Trending Topics to Content

4. RSS Batch Digest

5. Generate All Artifacts

6. Slides + Podcast → YouTube Video

Pipeline Workflows

MCP Server Setup

Claude Code Skill Setup

API Reference

CLI Commands (11)

MCP Tools (13)

Integrations

Contributing

License

Reviews