notebooklm-skill

Source-grounded NotebookLM automation for terminals and AI agents.

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notebooklm-skill gives humans and MCP clients one consistent interface for Google NotebookLM. It creates notebooks from URLs, raw text, and local files; asks grounded questions with citation metadata; completes fast or deep web research; and generates or downloads NotebookLM artifacts.

The project is built around notebooklm-py 0.7.x and includes:

• a JSON-first core CLI;
• five end-to-end research pipelines;
• a 13-tool FastMCP server;
• profile-aware authentication and Skill installers;
• one shared compatibility layer, so CLI, pipelines, and MCP use the same behavior.

This is an unofficial integration with NotebookLM's web API. Google can change the service, availability, quotas, or artifact behavior without notice.

Quick start

Isolated source install

The installer creates a dedicated virtual environment, installs Chromium, links five commands into ~/.local/bin, and installs the Claude Code Skill using the standard directory layout.

git clone https://github.com/claude-world/notebooklm-skill.git
cd notebooklm-skill
./install.sh

notebooklm-auth setup
notebooklm-skill list

Ensure ~/.local/bin is on PATH.

PyPI or uvx

# Persistent virtual environment
python3 -m venv .venv
source .venv/bin/activate
python -m pip install notebooklm-skill
python -m playwright install chromium
notebooklm-auth setup

# Or run without a persistent install
uvx --from notebooklm-skill notebooklm-auth setup
uvx --from notebooklm-skill notebooklm-skill list

Direct upstream login is also available:

uvx --from notebooklm-py notebooklm login

Sessions are profile-aware. Select one with --profile NAME before a CLI subcommand, or set NOTEBOOKLM_PROFILE.

To use the locally installed Google Chrome instead of bundled Chromium:

notebooklm-auth setup --browser chrome --fresh

Core CLI

All successful commands print structured JSON to stdout. Diagnostics go to stderr; authentication errors return exit code 4 and argument errors return exit code 2.

# Mixed-source ingestion with truthful per-source outcomes
notebooklm-skill create \
  --title "Research" \
  --sources https://example.com/article \
  --files ./paper.pdf \
  --text-sources "Interview notes" \
  --strict

notebooklm-skill ask \
  --notebook "Research" \
  --query "Which conclusions have the strongest evidence?"

notebooklm-skill research \
  --notebook "Research" \
  --query "Recent independent evaluations" \
  --mode deep --max-sources 10

notebooklm-skill generate \
  --notebook "Research" \
  --type slides --lang zh-TW \
  --output ./output/deck.pptx --output-format pptx

notebooklm-skill list-artifacts --notebook "Research" --type slides

Commands resolve an exact ID, unique title, or unique title substring. Use IDs for repeatable automation. Deletes require --yes; downloads refuse existing files or symlinks unless an explicit safe overwrite is requested with --force.

Artifact types