<div align="center">

NotebookLM REST API + MCP server

Automate Google NotebookLM at scale. 53-endpoint HTTP REST API for n8n / Zapier / Make / curl, plus an MCP server for Claude Code / Cursor / Codex. Citation-backed Q&A, full Studio generation (audio · video · infographic · report · presentation · data table), multi-account rotation with auto-reauth across personal and Google Workspace accounts.

v4.4.0 — Node 22 is now the floor, and the last four open advisories are gone with it. The declared floor of Node 18 had quietly become fiction: three production dependencies already required Node 20 or newer, and the test matrix kept passing on 18 without exercising them. Raising it also let the third-party file globber go — its dependency chain carried four advisories with no fix upstream — replaced by Node's built-in search, now actually under test. Builds on 4.0.0, where the HTTP API stopped being open to the network and to any web page (GHSA-p69m-c5rf-g2c3): it binds loopback, refuses unlisted origins, and takes a bearer token — remote access and Docker require `NOTEBOOKLM_API_KEY`, see Securing the HTTP API. Built on a dual transport — the internal batchexecute RPC API (10-100× faster than scraping, immune to UI rebrands) with the Playwright browser as an automatic fallback. See the changelog.

Note (July 2026): Google rebranded NotebookLM to Gemini Notebook. It is the same product, existing links redirect, and this project drives the same underlying service — the browser path was updated for the new DOM in v2.3.0 and the RPC path in v3.0.0. Package and repository keep the notebooklm name.

<!-- Badges -->

<!-- End Badges -->

</div>

Unofficial project — good to know before you start

>

This is not affiliated with Google. It talks to the same batchexecute endpoints the NotebookLM web app uses, with a browser fallback when they move. They are undocumented, so they can change without notice — when that happens we ship a fix, as we have for every change so far.

>

Two practical notes: use a dedicated Google account for automation, and expect NotebookLM's own quotas to apply at high volume. See Disclaimer for the full text.

What You Can Build

🔗 No-code automation pipelines — The 53-endpoint REST API means NotebookLM becomes a step in n8n, Zapier, Make, or a plain curl in cron. No agent, no MCP client, no Node in your stack — just HTTP. This is the half most NotebookLM libraries don't have.

🤖 Agent tooling — The same engine over MCP for Claude Code, Cursor and Codex, with a bundled skill that primes the agent on citation formats, the daily-quota-aware batch pattern, and transport selection.

📚 Research at volume — Multi-account rotation with automatic re-authentication, built for overnight runs of 1 000+ questions across several notebooks without babysitting.

🎙️ Full Studio generation — Audio overviews, video, infographics, reports, presentations, data tables, plus flashcards, quizzes and mind maps — generated and downloaded programmatically.

Use Cases & Recipes

NotebookLM is a grounded engine: Gemini reads your sources and answers _from them_, with citations. The winning pattern is to let it do the expensive reading while your own stack handles orchestration and the last mile.

Spend fewer tokens — offload the reading

• 🪙 Zero-token synthesis layer — Drop 30 documents in a notebook, let Gemini do the heavy analysis, and spend your agent's context only on the final polish. The reasoning happens server-side; your agent just orchestrates (add_notebook → source_add → notebook_ask).
• 💾 Answer cache you can re-read offline — vault_batch writes every answer to disk as structured JSON against a published schema, so a batch run becomes a corpus you can grep, diff, re-index, or feed to a retrieval layer — without re-querying and re-spending quota.

Wire it into things that aren't agents

• ⚙️ NotebookLM as an n8n / Zapier / Make step — Because it speaks plain HTTP, a citation-backed answer becomes one node in a workflow: a form submission triggers a question, the cited answer lands in a sheet, a Slack message, or a database. No agent runtime involved.
• 📄 Document intake pipeline — Watch a folder or an inbox, push new PDFs and URLs in as sources, and ask a standing set of questions against them on every arrival.

Grounded answers with a paper trail

• 🔍 Citations with the actual source text — Answers come back with source names _and the quoted excerpts_ they rest on, extracted from the citation panel — so a claim can be checked, not just attributed.
• 🎓 Literature review at thesis scale — Batch 100+ research questions across multiple notebooks, rotate accounts as daily quotas run out, and resume where it stopped. Built for, and tested on, exactly this.

Get artifacts back out

• 🔁 One source set, every format — Fan a single notebook out to a podcast, a video, a slide deck, a report, a quiz and a mind map, then download them all locally.

In the Wild

Real deployments, not hypotheticals.

• 📚 A doctoral literature review at batch scale — The project was built for, and is

continuously tested on, overnight runs of 1 000+ research questions spread across several notebooks: multi-account rotation picks up when a daily quota runs out, every answer is written to disk with its citations, and an interrupted run resumes instead of starting over. The batch pattern in vault_batch exists because a thesis needed it.

• 🔌 Replacing a RAG engine with the REST API — musnymubarak/Calim_Doc

swapped a Gemini-based retrieval engine for this project's HTTP API, running it as a Docker service (notebooklm:3000) behind a full client and worker layer. A good illustration of the REST half: no agent runtime, no MCP client — NotebookLM simply became a backend service their Python app calls.

Built something with it? Open an issue — this section is for other people's work.

Features

Q&A with Citations

• Ask questions to NotebookLM and get accurate, citation-backed answers
• Source citation extraction with 5 formats: none, inline, footnotes, json, expanded (97% excerpt success rate)
• Session management for multi-turn conversations with auto-reauth on session expiry

Content Generation

Generate multiple content types from your notebook sources:

Video Visual Styles: classroom, documentary, animated, corporate, cinematic, minimalist

Language of generated content: pass language to any generator — a BCP-47 code (es, ja, pt_BR, zh_Hans) or a name in English or in the language itself ("Spanish", "Español"). 81 languages are accepted, and an unrecognised one is refused rather than quietly swapped for another. Set a default with NOTEBOOKLM_CONTENT_LANGUAGE; it is deliberately independent of NOTEBOOKLM_UI_LOCALE, which only picks the interface language the browser fallback reads.

Flashcards and quizzes are generated via generate_study_aid; mind maps via generate_mind_map. v3 also adds share_notebook, manage_labels, and research_sources (web/Drive source discovery) — see the changelog.

Content Download

• Download Audio — WAV audio files
• Download Video — MP4 video files
• Download Infographic — PNG image files
• Text-based content (report, presentation, data_table) is returned in the API response
• Delete generated content (content_delete) — until now a notebook accumulated every draft anyone ever asked for, with no way to remove one short of the web UI

Source Management

• Add sources: Files (PDF, TXT, DOCX), URLs, Text, YouTube videos, Google Drive
• List sources: Every source with its ID and title (source_list)
• Rename a source (rename_source): fix a title in place, by id or by name
• Check freshness (check_source_freshness): which URL / Drive sources have drifted from what they point at — the whole notebook in one call. An unanswered source is reported as unknown, never as current
• Read a source's guide (get_source_guide): NotebookLM's own summary and key topics for one source
• Read a source in full (source_read): the exact text NotebookLM indexed — what it actually reasons over, which the web UI only shows in fragments. Quote a source verbatim, check what a PDF really yielded, or hand the raw material to another tool. Name the source instead of its ID if you prefer; an ambiguous name is refused rather than guessed. Long sources arrive one page at a time, with an explicit instruction for fetching the next — or paginate: false for the whole document at once.

Notebook Summary and Chat History

• What is in this notebook? (get_notebook_summary) — NotebookLM's own summary of its sources plus the questions it suggests asking, without spending a question to find out
• What was already asked? (get_chat_history) — read back the recorded questions and answers, newest first. An agent resuming work stops paying to ask what it already asked. NotebookLM exposes only the most recent conversation per notebook
• Clear the history (delete_chat_history) — the web UI's "Delete history". There is no per-turn delete: the whole conversation goes

Artifact Export and Revision

• Export to Drive (export_artifact) — send a finished artifact to Google Docs or Google Sheets
• Revise one slide (revise_slide) — change a single slide from a prompt instead of regenerating the whole deck

Notebook Library

• Multi-notebook management with validation and smart selection
• Auto-discovery: Automatically generate metadata via NotebookLM queries
• Search notebooks by keyword in name, description, or topics
• Scrape notebooks: List all notebooks from NotebookLM with IDs and names
• Bulk delete: Delete multiple notebooks at once

Accounts & Localization

• Personal _and_ Google Workspace accounts — recognizes both NotebookLM hosts (notebooklm.google.com and the notebook.google.com Workspace alias), so Workspace sessions authenticate cleanly instead of looping on "session expired"
• UI-language-aware — drives NotebookLM whether its interface is in English, French, German, or Japanese (en · fr · de · ja); add a language in a single JSON file

Integration Options

• MCP Protocol — Claude Code, Cursor, Codex, any MCP client
• Agent Skill — ships a bundled notebooklm skill (also standalone: roomi-fields/notebooklm-skill) that teaches the agent citation formats, the batch-to-cache pattern, and when to use which transport
• HTTP REST API — n8n, Zapier, Make.com, custom integrations
• Docker — Isolated deployment with Docker or Docker Compose
• [RTFM](https://github.com/roomi-fields/rtfm) retrieval layer — /batch-to-vault writes citation-backed answers as markdown + JSON sidecars (nblm-answer-v1 schema), indexable by RTFM (FTS5 + semantic) for unlimited offline queries. Ideal for academic / SOTA workflows. Guide.

Quick Start

Option 0 — Claude Code marketplace (one-liner, recommended for Claude Code users)

The fastest way to get NotebookLM into Claude Code. Distributed via the roomi-fields/claude-plugins marketplace alongside RTFM (the retrieval companion — see RTFM integration guide):

/plugin marketplace add roomi-fields/claude-plugins
/plugin install notebooklm@roomi-fields

That registers the MCP server and the `notebooklm` agent skill, runs npx -y @roomi-fields/notebooklm-mcp@<pinned-version> automatically (Node ≥ 22 required), and lets you upgrade with two commands when a new release ships: /plugin marketplace update roomi-fields then /reload-plugins. Then run npx -y -p @roomi-fields/notebooklm-mcp notebooklm-mcp-setup-auth once in a terminal to log into Google (a visible Chrome opens). To install RTFM at the same time: /plugin install rtfm@roomi-fields.

Option 1 — HTTP REST API (n8n, Zapier, Make, curl, any HTTP client)

git clone https://github.com/roomi-fields/notebooklm-mcp.git
cd notebooklm-mcp
npm install && npm run build
npm run setup-auth   # One-time Google login
npm run start:http   # Start REST API on port 3000

# Citation-backed Q&A, single curl, JSON response
curl -X POST http://localhost:3000/ask \
  -H 'Content-Type: application/json' \
  -d '{"question": "Summarize chapter 3", "notebook_id": "your-id", "source_format": "json"}'

The full surface is 33 documented endpoints — see the REST API reference. For overnight batches of 1 000+ questions, see the batch pattern.

Option 2 — MCP Mode (Claude Code, Cursor, Codex)

# Build (same package, MCP transport)
git clone https://github.com/roomi-fields/notebooklm-mcp.git
cd notebooklm-mcp
npm install && npm run build

# Claude Code
claude mcp add notebooklm node /path/to/notebooklm-mcp/dist/index.js

# Cursor — add to ~/.cursor/mcp.json
{
  "mcpServers": {
    "notebooklm": {
      "command": "node",
      "args": ["/path/to/notebooklm-mcp/dist/index.js"]
    }
  }
}

Log in once — in a terminal, not through the assistant. Run the interactive Google login as a command; a visible Chrome window opens, you sign in, and the saved session is then reused by the MCP server:

npm run setup-auth          # from a clone (Option 2 above)
notebooklm-mcp setup-auth   # from a global install (npm i -g @roomi-fields/notebooklm-mcp)

Do the login in a terminal rather than by asking the assistant _"log me in"_: some stdio MCP clients (e.g. Claude Desktop) cap tool-call duration and cut off the up-to-10-minute interactive login before you can finish signing in (see issue #27).

Option 3 — Docker (NAS, server, headless)

# Build and run
docker build -t notebooklm-mcp .
docker run -d --name notebooklm-mcp -p 3000:3000 -p 6080:6080 -v notebooklm-data:/data notebooklm-mcp

# Authenticate via noVNC
# 1. Open http://localhost:6080/vnc.html
# 2. Run: curl -X POST http://localhost:3000/setup-auth -d '{"show_browser":true}'
# 3. Login to Google in the VNC window

See Docker Guide for NAS deployment (Synology, QNAP).

Documentation

Full docs site: <https://notebooklm.roomi-fields.com/> · OpenAPI 3.1 spec

Roadmap

See ROADMAP.md for planned features and version history.

Latest releases:

• v3.0.1 — Interactive Google login as a first-class CLI command (notebooklm-mcp setup-auth) for global / stdio-client installs; setup_auth / re_auth accept a top-level headless (#27)
• v3.0.0 — Major refactor: dual transport (NotebookLM's internal batchexecute RPC API with automatic DOM fallback), 10-100× faster and immune to UI rebrands; 5 new tools (notebook sharing, study aids, mind maps, source labels, web research)
• v2.3.0 — Full support for Google's "Gemini Notebook" rebrand: create / list / rename / delete, sources, and every Studio generation type re-verified end-to-end (#23, #21)
• v2.2.1 — Recognize both NotebookLM hosts so Google Workspace accounts authenticate (the notebook.google.com alias); notebook listing no longer wastes ~30s after the "Gemini Notebook" rebrand; HTTP banner reads the real version. Diagnosis + patch by @kpietkaa (#19)
• v2.2.0 — Fix new-answer detection timing out when an answer repeats an earlier one (position-based identity, not text-hash); graceful shutdown on stdio disconnect; Japanese UI locale
• v2.1.1 — Thai UI selectors for notebook_create (partial, #18)
• v2.1.0 — note_list and note_get MCP tools (#17)
• v2.0.4 — German UI selectors (closes #14)
• v2.0.0 — Tools renamed to a namespaced tree (notebook_ask, source_add, session_list, server_health, vault_batch…) across 9 namespaces; tools/list advertises only the canonical names. Backward compatible — the legacy flat names still work as aliases, so existing scripts and configs keep running. Also adds MCP annotations (read-only / destructive / idempotent / open-world hints) and outputSchema + structuredContent on every tool. Published on the Smithery registry.
• v1.7.0 — batch_to_vault exposed as a first-class MCP tool (parity with the HTTP endpoint, no localhost server required); shared runBatchToVault helper deduplicates the loop across both transports
• v1.6.0 — /batch-to-vault endpoint + RTFM integration (nblm-answer-v1 JSON Schema published at schemas.roomi-fields.com/nblm-answer-v1.json) for caching NotebookLM answers as a searchable markdown vault
• v1.5.8 — NotebookLM 2026 UI adaptations (icon-label sanitization, Discussion-panel recovery, count-based source detection) — PR #5 by @KhizarJamshaidIqbal
• v1.5.7 — Citation extraction selector fix (.highlighted) and Docker multi-stage build — PR #1 by @JulienCANTONI
• v1.5.6 — Citation extraction major rewrite (97% success rate), browser-verified auth at startup, profile auto-sync
• v1.5.0 — Complete Studio content generation (video, infographic, presentation, data_table) + Notes management + Delete sources
• v1.4.0 — Content management (sources, audio, generation) + Multi-account

_Intermediate patch and hardening releases (1.5.x–1.7.x) are in the full CHANGELOG._

Not yet implemented:

• Discover sources (Web/Drive search with Fast/Deep modes)
• Edit notes (create, delete, and convert are implemented)

Disclaimer

This tool automates browser interactions with NotebookLM. Use a dedicated Google account for automation. CLI tools like Claude Code can make mistakes — always review changes before deploying.

See full Disclaimer below.

Contributing

Found a bug? Have an idea? Open an issue or submit a PR!

See CONTRIBUTING.md for guidelines.

License

MIT — Use freely in your projects. See LICENSE.

Author

Romain Peyrichou — @roomi-fields

Acknowledgments

Thanks to everyone who has contributed code, ideas, and bug reports:

• Khizar Jamshaid Iqbal — @KhizarJamshaidIqbal, 2025 UI selector fixes, doctor script, PII scrub
• Kazik Pietka — @kpietkaa, notebook.google.com rebrand support
• Rui Ruiberriz — @Excauboi, hl=<uiLocale> on app URLs + click-through scrape fallback
• [@he0xwhale](https://github.com/he0xwhale) — note_list / note_get MCP tools
• [@eminsnow](https://github.com/eminsnow) — canonical tool names (_ over .)
• Julien Cantoni — @JulienCANTONI

<details> <summary><a name="disclaimer-details"></a>Full Disclaimer</summary>

About browser automation: While I've built in humanization features (realistic typing speeds, natural delays, mouse movements), I can't guarantee Google won't detect or flag automated usage. Use a dedicated Google account for automation.

About CLI tools and AI agents: CLI tools like Claude Code, Codex, and similar AI-powered assistants are powerful but can make mistakes:

• Always review changes before committing or deploying
• Test in safe environments first
• Keep backups of important work
• AI agents are assistants, not infallible oracles

I built this tool for myself and share it hoping it helps others, but I can't take responsibility for any issues that might occur. Use at your own discretion.

</details>

<div align="center">

Built with frustration about hallucinated APIs, powered by Google's NotebookLM

⭐ Star on GitHub if this saves you debugging time!

</div>