Which integrations are available for this server?

Supports using arXiv paper URLs as sources for NotebookLM research. Supports using RSS feeds as sources for NotebookLM research. Allows publishing research-backed social posts to Threads via the threads-viral-agent integration. Supports adding YouTube videos as sources for NotebookLM research.

How do I use notebooklm-skill?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@notebooklm-skill Research https://example.com and summarize findings" 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.

notebooklm-skill

by claude-world

Overview Schema Related Servers Score Discussions

Python

Local

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.

License: MIT

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

# Option A: uvx (recommended — zero install)
uvx notebooklm-skill --help
uvx --from notebooklm-skill notebooklm-mcp   # Start MCP server

# Option B: pip install from PyPI
pip install notebooklm-skill

# Option C: Install from source
git clone https://github.com/claude-world/notebooklm-skill.git
cd notebooklm-skill && pip install .

# Option D: One-line install (pip + Playwright + Claude Code Skill)
git clone https://github.com/claude-world/notebooklm-skill.git
cd notebooklm-skill && ./install.sh

# Authenticate with Google (one-time, opens browser)
uvx notebooklm login              # if using uvx
# or: python3 -m notebooklm login  # if using pip install

# Use commands (uvx or direct — both work the same)
notebooklm-skill create --title "My Research" --sources https://example.com/article
notebooklm-skill ask --notebook "My Research" --query "What are the key findings?"
notebooklm-skill podcast --notebook "My Research" --lang en --output podcast.m4a
notebooklm-pipeline research-to-article --sources https://example.com --title "Topic"
notebooklm-mcp                   # Start MCP server (stdio mode)

Or use scripts directly: python scripts/notebooklm_client.py create ...

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

Authentication

notebooklm-py uses browser-based Google login. No API keys, no OAuth Client ID, no Google Cloud project needed.

# One-time login (opens Chromium, sign in with Google)
uvx notebooklm login              # if using uvx
python3 -m notebooklm login       # if using pip install

Step	Command	What happens
Login	`uvx notebooklm login`	Opens Chromium, user logs into Google
Session storage	Automatic	Saved to `~/.notebooklm/storage_state.json`
Subsequent use	All CLI / MCP commands	Reads saved session, pure HTTP calls
Verify	`uvx notebooklm-skill list`	Lists notebooks to confirm auth works
Clear	`rm -rf ~/.notebooklm`	Removes stored session

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 (9 downloadable types)

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

Most artifacts support language selection (e.g., --lang zh-TW). Exceptions: quiz, flashcards, mind-map.

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| ⚠️ no download    |
|                               | 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"

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

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": "uvx",
      "args": ["--from", "notebooklm-skill", "notebooklm-mcp"]
    }
  }
}

Or if you installed via pip install notebooklm-skill:

{
  "mcpServers": {
    "notebooklm": {
      "command": "notebooklm-mcp"
    }
  }
}

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

Claude Code Skill Setup

# Option A: Symlink (auto-updates with git pull)
./install.sh

# Option B: Manual copy
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 (9 types, infographic excluded)
`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 -e .
python3 -m notebooklm login
python -m pytest tests/

License

MIT License. See LICENSE.

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

2dRelease cycle

5Releases (12mo)

Resources

GitHub Repository

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notebooklm-skill

Demo

What is this?

Quick Start

Authentication

Two Ways to Use

Features

Artifact Generation (9 downloadable 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

Maintenance

Resources

Looking for Admin?

Latest Blog Posts

MCP directory API