Open NotebookLM

Use your own signed-in Google NotebookLM account (now called Gemini Notebook, notebook.google.com) from AI agents, scripts and the terminal, with no GUI. It works as an MCP server, a CLI, a local REST API and an OpenAI-compatible API.

You sign in once in a normal Chrome window. After that, Open NotebookLM keeps a hidden Chrome tab and calls the same internal endpoints the NotebookLM web app calls, from inside that tab. Your agent can do everything a person does in the UI: create notebooks, add sources, chat with citations, run Deep Research, and make Audio/Video Overviews, slide decks, quizzes, flashcards, mind maps, infographics, reports and data tables, then download them. It never asks for your password, and no cookies leave your browser.

your agent ──MCP / CLI / REST / OpenAI──▶ open-notebooklm (127.0.0.1:2791) ──▶ hidden Chrome tab on notebook.google.com

AI agents: read skills/open-notebooklm/SKILL.md. It covers setup, every tool, recipes and limits. Give your agent this repo's link and it can set itself up.

What it can do

Everything below was tested end to end against a live Google AI Pro account in October 2026. The two exceptions are sharing with another person (not tested, to avoid emailing anyone) and retrying a failed output (no output failed during testing).

* Cinematic video needs Google AI Ultra. What each plan allows: docs/plans-and-limits.md. How it was reverse-engineered: docs/how-it-works.md.

Related MCP server: gemini-notebook-mcp

Before you use it

• This is unofficial and not affiliated with Google. It automates notebook.google.com with your own login. Use it on your own account for personal use. Google can change its internal API at any time.

• It uses your account's real quotas (for example, about 3 Audio Overviews a day on the free plan).

• Files you pass are local paths on the machine running Open NotebookLM. It only listens on 127.0.0.1.

Setup

Needs Node.js 20+ and Google Chrome (or Chromium). Set CHROME_PATH if Chrome isn't in the usual place.

git clone https://github.com/mkshaonexe/open-notebooklm.git
cd open-notebooklm
npm install
npm link        # optional: puts `open-notebooklm` (alias `notebooklm`) on your PATH

1. Sign in once. A Chrome window opens on NotebookLM; sign in to Google the normal way:

open-notebooklm login

The session is kept in ~/.open-notebooklm/chrome-profile, a separate Chrome profile only Open NotebookLM uses.

2. Use it. Every command works on its own (it starts a hidden Chrome when needed), or start the server once and keep it running:

open-notebooklm serve           # hidden Chrome; --show to see the window

It prints the URL and your local API key (open-notebooklm key prints the key again).

CLI

<nb> is a notebook id or part of its title.

open-notebooklm notebooks
open-notebooklm create "Solar research"
open-notebooklm add "Solar" https://en.wikipedia.org/wiki/Solar_power https://youtu.be/xKxrkht7CpY ./notes.pdf \
  --text "Bangladesh has 6M+ solar home systems." --title "My note"
open-notebooklm research "Solar" "solar panel recycling methods" --deep      # finds + imports sources and a report
open-notebooklm ask "Solar" "What are the main challenges?"                  # answer + [1] [2] citations
open-notebooklm summary "Solar"

open-notebooklm generate "Solar" audio --format debate --length short -o podcast.m4a   # waits, then downloads
open-notebooklm generate "Solar" video --format explainer --style whiteboard -o video.mp4
open-notebooklm generate "Solar" slide_deck --format presenter_slides -o deck.pdf
open-notebooklm generate "Solar" infographic --orientation portrait --style kawaii -o info.png
open-notebooklm generate "Solar" report --format study_guide -o guide.md
open-notebooklm generate "Solar" quiz --quantity more --difficulty hard -o quiz.json
open-notebooklm generate "Solar" flashcards --wait
open-notebooklm generate "Solar" mind_map -o map.json
open-notebooklm generate "Solar" data_table -i "compare each technology by efficiency and cost" -o table.csv

open-notebooklm artifacts "Solar"                    # every output and its status
open-notebooklm download "Solar" <artifact_id> -o deck.pptx --format pptx
open-notebooklm export "Solar" <report_id>           # → Google Docs link (--sheets for data tables)
open-notebooklm revise-slide "Solar" <deck_id> 2 "Make this a 3-bullet summary"

open-notebooklm sources "Solar" ; source "Solar" <source_id> ; search "Solar" "perovskite"
open-notebooklm notes "Solar" ; add-note "Solar" "Idea" "Check IDCOL data"
open-notebooklm share "Solar" --public               # --private, --add a@b.com --role viewer, --chat-only
open-notebooklm usage                                # live 5-hour / weekly meter
open-notebooklm account                              # plan, limits, output language

Long commands print progress on stderr (… generating audio (in_progress) (40s); --quiet hides it). --json prints the full result. Without -o/--wait, generate returns at once with the artifact id.

MCP

stdio (simplest: it starts the hidden Chrome itself, or forwards to a running serve):

claude mcp add notebooklm -- node /path/to/open-notebooklm/bin/cli.js mcp

{ "mcpServers": { "notebooklm": { "command": "node", "args": ["/path/to/open-notebooklm/bin/cli.js", "mcp"] } } }

(after npm link: "command": "open-notebooklm", "args": ["mcp"])

Streamable HTTP (with serve running):

claude mcp add --transport http notebooklm http://127.0.0.1:2791/mcp \
  --header "Authorization: Bearer $(open-notebooklm key)"

51 tools, all prefixed notebooklm_. The full list with arguments is in SKILL.md. Long tools (ask, add_sources, research, generate, wait_for_artifact, download_artifact) send MCP progress notifications when the client passes a progressToken. Failures come back as error results that name the step and the reason, for example Failed while generating audio: NotebookLM usage limit reached for this account (5-hour window resets …).

Agent skill

skills/open-notebooklm/SKILL.md is a standard agent skill. Copy the skills/open-notebooklm folder into your agent's skills directory (for Claude Code: ~/.claude/skills/), or just point your agent at this repository: AGENTS.md tells it where to start.

REST

Every route except /health needs Authorization: Bearer <key>. The API is one route per method: POST /api/<method> with the method's options as a JSON body (camelCase). The CLI and the MCP server use the same methods.

KEY=$(open-notebooklm key)
curl -s localhost:2791/api/listNotebooks -H "authorization: Bearer $KEY" -d '{}'
curl -s localhost:2791/api/ask -H "authorization: Bearer $KEY" -H 'content-type: application/json' \
  -d '{"notebookId":"<id>","question":"Summarise the sources in 3 bullets"}'
curl -s localhost:2791/api/generate -H "authorization: Bearer $KEY" -H 'content-type: application/json' \
  -d '{"notebookId":"<id>","type":"audio","format":"brief","wait":true}'

All notebook-scoped methods take notebookId.

OpenAI-compatible API

Each notebook is a "model". Answers are grounded in that notebook's sources, and the citations are listed at the end of the reply.

from openai import OpenAI
client = OpenAI(base_url="http://127.0.0.1:2791/v1", api_key="<open-notebooklm key>")
print([m.id for m in client.models.list()])          # notebook:<id> for every notebook
r = client.chat.completions.create(model="notebook:<notebook_id>",
                                   messages=[{"role": "user", "content": "What do my sources say about X?"}])
print(r.choices[0].message.content)

Only the newest user message is sent; the notebook keeps its own chat history.

Files and settings

Everything lives in ~/.open-notebooklm/ (override with OPEN_NOTEBOOKLM_HOME):

If Google renames an internal RPC id, you can patch it without a new release: OPEN_NOTEBOOKLM_RPC_OVERRIDES='{"LIST_NOTEBOOKS":"newId"}' (names are in src/rpc.js).

Credits

Built with the capture-the-traffic approach of reverse-api-engineer. The RPC map was cross-checked against the excellent reverse-engineering notes of notebooklm-py (MIT), and every call was verified against the live site. Same pattern as open-chatgpt.

License

MIT