A Comprehensive NotebookLM Skill & Unofficial Python API. Full programmatic access to NotebookLM's features—including capabilities the web UI doesn't expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw.

Source & Development: https://github.com/teng-lin/notebooklm-py

⚠️ Unofficial Library - Use at Your Own Risk

This library uses undocumented Google APIs that can change without notice.

• Not affiliated with Google - This is a community project
• APIs may break - Google can change internal endpoints anytime
• Rate limits apply - Heavy usage may be throttled

Best for prototypes, research, and personal projects. See Troubleshooting for debugging tips.

🤖 AI Agent Tools - Integrate NotebookLM into Claude Code, Codex, and other LLM agents. Ships with a root NotebookLM skill for GitHub and npx skills add discovery, local notebooklm skill install support for Claude Code and .agents skill directories, and repo-level Codex guidance in AGENTS.md.

📚 Research Automation - Bulk-import sources (URLs, PDFs, YouTube, Google Drive), run web/Drive research queries with auto-import, and extract insights programmatically. Build repeatable research pipelines.

🎙️ Content Generation - Generate Audio Overviews (podcasts), videos, slide decks, quizzes, flashcards, infographics, data tables, mind maps, and study guides. Full control over formats, styles, and output.

📥 Downloads & Export - Download all generated artifacts locally (MP3, MP4, PDF, PNG, CSV, JSON, Markdown). Export to Google Docs/Sheets. Features the web UI doesn't offer: batch downloads, quiz/flashcard export in multiple formats, mind map JSON extraction.

These features are available via API/CLI but not exposed in NotebookLM's web interface:

• Batch downloads - Download all artifacts of a type at once
• Quiz/Flashcard export - Get structured JSON, Markdown, or HTML (web UI only shows interactive view)
• Mind map data extraction - Export hierarchical JSON for visualization tools
• Data table CSV export - Download structured tables as spreadsheets
• Slide deck as PPTX - Download editable PowerPoint files (web UI only offers PDF)
• Slide revision - Modify individual slides with natural-language prompts
• Report template customization - Append extra instructions to built-in format templates
• Save chat to notes - Save Q&A answers or conversation history as notebook notes
• Source fulltext access - Retrieve the indexed text content of any source
• Programmatic sharing - Manage permissions without the UI
• Multi-account profiles - Switch between Google accounts without re-authenticating
• Browser cookie import - Reuse cookies from your existing browser session instead of driving Playwright

The full install guide — six personas (agent, end-user, library, headless, contributor, power-user), optional extras matrix, platform notes — lives in docs/installation.md.

Quickest start (CLI users and AI agents):

pip install "notebooklm-py[browser]"   # core + Playwright
playwright install chromium             # ~170 MB; no progress bar — be patient (30–90 s)
notebooklm login                        # opens browser for Google sign-in
notebooklm auth check --test --json     # verify: expect "status": "ok"

As a library (embedded in your app — no Playwright, no Chromium):

pip install notebooklm-py               # ~10 MB; ship a pre-acquired storage_state.json

If playwright install chromium fails on Linux with TypeError: onExit is not a function, see the Linux workaround. Contributors: see CONTRIBUTING.md.

16-minute session compressed to 30 seconds

# 1. Authenticate (opens browser)
notebooklm login
# Or use Microsoft Edge (for orgs that require Edge for SSO)
# notebooklm login --browser msedge
# Or reuse cookies from an already-logged-in browser session
# notebooklm login --browser-cookies chrome
# notebooklm login --browser-cookies 'chrome::Profile 1'  # one Chromium profile
# (combine with --profile to populate a specific profile;
#  use --account / --all-accounts after auth inspect when several
#  Google accounts are signed in)

# 2. Create a notebook and add sources
notebooklm create "My Research"
notebooklm use <notebook_id>
notebooklm source add "https://en.wikipedia.org/wiki/Artificial_intelligence"
notebooklm source add "./paper.pdf"

# 3. Chat with your sources
notebooklm ask "What are the key themes?"
notebooklm ask --prompt-file ./long_question.txt  # Read question from file

# 4. Generate content (use --prompt-file for long prompts)
notebooklm generate audio "make it engaging" --wait
notebooklm generate video --style whiteboard --wait
notebooklm generate cinematic-video "documentary-style summary" --wait
notebooklm generate quiz --difficulty hard
notebooklm generate flashcards --quantity more
notebooklm generate slide-deck
notebooklm generate infographic --orientation portrait
notebooklm generate mind-map
notebooklm generate data-table "compare key concepts"

# 5. Download artifacts
notebooklm download audio ./podcast.mp3
notebooklm download video ./overview.mp4
notebooklm download cinematic-video ./documentary.mp4
notebooklm download quiz --format markdown ./quiz.md
notebooklm download flashcards --format json ./cards.json
notebooklm download slide-deck ./slides.pdf
notebooklm download infographic ./infographic.png
notebooklm download mind-map ./mindmap.json
notebooklm download data-table ./data.csv

Other useful CLI commands:

notebooklm auth check --test         # Diagnose auth/cookie issues
notebooklm auth refresh --quiet      # One-shot cookie keepalive (for cron / launchd / systemd)
notebooklm auth refresh --browser-cookies chrome  # Re-extract and repair account routing
notebooklm auth inspect --browser 'chrome::Profile 1'  # Preview one Chromium profile
notebooklm agent show codex          # Print bundled Codex instructions
notebooklm agent show claude         # Print bundled Claude Code skill template
notebooklm language list             # List supported output languages
notebooklm metadata --json           # Export notebook metadata and sources
notebooklm share status              # Inspect sharing state
notebooklm source add-research "AI"  # Start web research and import sources
notebooklm skill status              # Check local agent skill installation
notebooklm profile list              # List all Google account profiles
notebooklm profile switch work       # Switch active account profile

Use --prompt-file PATH with ask, prompt-based generate commands, and source add-research when the text is too long for the shell command line. This reads prompt/query text from a file and is separate from source add ./file.pdf, which still uploads that file as a NotebookLM source.

import asyncio
from notebooklm import NotebookLMClient

async def main():
    async with await NotebookLMClient.from_storage() as client:
        # Create notebook and add sources
        nb = await client.notebooks.create("Research")
        await client.sources.add_url(nb.id, "https://example.com", wait=True)

        # Chat with your sources
        result = await client.chat.ask(nb.id, "Summarize this")
        print(result.answer)

        # Generate content (podcast, video, quiz, etc.)
        status = await client.artifacts.generate_audio(nb.id, instructions="make it fun")
        await client.artifacts.wait_for_completion(nb.id, status.task_id)
        await client.artifacts.download_audio(nb.id, "podcast.mp3")

        # Generate quiz and download as JSON
        status = await client.artifacts.generate_quiz(nb.id)
        await client.artifacts.wait_for_completion(nb.id, status.task_id)
        await client.artifacts.download_quiz(nb.id, "quiz.json", output_format="json")

        # Generate mind map and export
        result = await client.artifacts.generate_mind_map(nb.id)
        await client.artifacts.download_mind_map(nb.id, "mindmap.json")

asyncio.run(main())

Option 1 — CLI install:

notebooklm skill install

Installs the skill into ~/.claude/skills/notebooklm and ~/.agents/skills/notebooklm.

Option 2 — npx install (via the open skills ecosystem):

npx skills add teng-lin/notebooklm-py

Fetches the canonical SKILL.md directly from GitHub.

• CLI Reference - Complete command documentation
• Python API - Full API reference
• Configuration - Storage and settings
• Release Guide - Release checklist and packaging verification
• Troubleshooting - Common issues and solutions
• API Stability - Versioning policy and stability guarantees

• Development Guide - Architecture, testing, and releasing
• RPC Development - Protocol capture and debugging
• RPC Reference - Payload structures
• Changelog - Version history and release notes
• Security - Security policy and credential handling

MIT License. See LICENSE for details.