notebooklm-skill combines NotebookLM’s research capabilities with Claude Code. Just throw in a batch of URLs, PDFs, or trending topics, and it automatically creates notes, conducts research, and organizes them into structured information. Then, with that content, you can have Claude write articles, tweets, newsletters, or any text format you want.

GitHub: http://github.com/claude-world/notebooklm-skill…

In addition to being used as a Claude Code Skill, it can also run as an independent MCP service, integrated into your own agent workflow. It can also generate podcast audio, slides, mind maps, etc., saving content creators a lot of time.

claude-world/notebooklm-skill

Source: https://github.com/claude-world/notebooklm-skill

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

Traditional Chinese README

Demo

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 (https://pypi.org/project/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

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

Two Ways to Use

Features

Artifact Generation (9 downloadable types)

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"

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

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)

MCP Tools (13)

Integrations

• trend-pulse (https://github.com/claude-world/trend-pulse) — Real-time trending topic discovery from 7 sources
• threads-viral-agent (https://github.com/claude-world/claude-world.com) — Auto-publish research-backed social posts

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes
4. 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.