A Comprehensive Google Gemini Notebook 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.
$ npx -y skills add teng-lin/notebooklm-py --agent claude-code
What's inside
A Comprehensive Google Gemini Notebook 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.
Note (July 2026): Google rebranded NotebookLM to Gemini Notebook. It remains the same standalone product (now also reachable inside the Gemini app), existing links redirect automatically, and this library drives the same underlying service and works unchanged. The package keeps the
notebooklm-pyname.
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.
NotebookLM is a grounded engine: Gemini does the heavy reading and answers from your sources with citations. The winning pattern is to let it do the expensive analysis while your agent (Claude Code, Codex, …) orchestrates and handles the final mile — using NotebookLM as a zero-token synthesis + memory layer an agent drives in a loop, and pulling structured artifacts out in bulk and in richer, scriptable formats. Recipes people build on top of this library, grouped by what they use NotebookLM as:
Spend fewer tokens — let NotebookLM do the expensive thinking:
create → source add → ask); the reasoning happens server-side. In the wild: a four-workflow guide to stop Claude Code burning tokens on NotebookLM.source add-research "your topic" --mode deep) or load a doc corpus, let NotebookLM's Gemini condense it, and bake the result into a SKILL.md your agent loads at startup — build once, reuse with zero runtime tokens or network calls, git-versioned and immune to UI drift. A packaged domain expert without hand-curating sources. (Dumping raw docs into a skill flattens the hierarchy; NotebookLM condensing first is what makes it work.)Give your agent memory — persistent, grounded recall:
note create / ask --save-as-note), and a line in your CLAUDE.md queries it (ask) at the start of the next session. Storage and recall live on Google's infrastructure.ask) so an agent answers from your code with citations rather than plausible-sounding guesses — a zero-infra alternative to standing up your own vector DB and embedding pipeline. In the wild: turning a notebook into the source-grounded "project brain" a coding agent consults before it writes code.ask for cited answers across your own history — surfacing long-term patterns a keyword search can't (e.g. a weekly summary synthesized from 282 daily notes, every claim linked back to the entry it came from). In the wild: chatting with a year of daily notes as a cited knowledge base.Turn your sources into answers & artifacts — cited responses, generated media, and exports:
ask --json for source-grounded, cited answers for support, on-call, or internal Q&A. Or have an agent point it at an entire fast-moving tool's docs — more than the agent can hold in context — as a troubleshooting oracle it queries the moment it hits an error. In the wild: OpenClaw drove the library to scrape all 524 pages of docs.openclaw.ai, dedupe the duplicate translations, and audit it down to 269 clean sources (missing/extra/duplicate = 0).generate audio (podcast), generate video, generate slide-deck, plus a generate report blog draft, generate quiz, and generate flashcards — fan a single notebook out across channels.download <type> / download <type> --all). The programmatic "get data out" half of the library, not just "put sources in."[[wikilinks]]. Pair with a podcast overview for an audio digest of your notes. In the wild: "Claude Code + NotebookLM + Obsidian = GOD MODE".Run it unattended, at scale, or on the go — scheduled, headless, and remote:
generate report --format briefing-doc --wait, then download report) as an automated runbook.auth refresh --quiet (cron/launchd/systemd) with generate audio to publish a fresh personalized briefing to a podcast feed on a schedule.These combine ordinary library primitives — see the CLI Reference and Python API. The agent-side glue (skills, scheduling, vault layout) lives in your own setup, not this package. Per-notebook source counts depend on your Google account tier — split across notebooks if you hit a cap.
New here? Start with a walkthrough: Claude Code + NotebookLM = CHEAT CODE (video) · 5 demos + 50 use cases, with prompts.
| Method | Best For |
|---|---|
| Python API | Application integration, async workflows, custom pipelines |
| CLI | Shell scripts, quick tasks, CI/CD automation |
| MCP Server | Claude Desktop/Code, Codex, etc. — locally via stdio, or as a self-hosted remote connector (behind a Cloudflare/Tailscale tunnel) reachable from claude.ai and ChatGPT, mobile included. |
| REST Server | Local automation over guarded HTTP routes without spawning a CLI process per call |
| Agent Integration | Claude Code, Codex, LLM agents, natural language automation |
The default backend is the established Web (batchexecute) transport. This
release also provides an opt-in Android backend that uses NotebookLM's mobile
gRPC service and bearer authentication. Select it for the CLI with
--backend android (or NOTEBOOKLM_BACKEND=android), or for the Python API
with NotebookLMClient.from_storage(backend="android") / NotebookLMClient(..., backend="android").
Install the Android runtime explicitly; it is intentionally not included in
the all extra:
pip install "notebooklm-py[android,browser]"
notebooklm login --master-token --account you@example.com
notebooklm --backend android list --json
Android reads master_token.json from the selected profile and mints
short-lived mobile bearer tokens as needed, so typed namespace calls do not
depend on a browser-cookie session, Web build labels, or Web RPC IDs. All
eleven public namespaces are available without falling back to the Web
transport. Because the durable master token is a powerful full-account
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@teng-linFAQ
notebooklm-py is a Claude Code plugin with 1 hand-picked skill for development work, indexed on Flowy. Install it with the command on its page. It includes notebooklm-py. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
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