// Query, manage, and automate Google NotebookLM from your AI agent. Add sources, generate slide decks with your brand colors, run research, and keep auth alive automatically.
| name | notebooklm |
| description | Query, manage, and automate Google NotebookLM from your AI agent. Add sources, generate slide decks with your brand colors, run research, and keep auth alive automatically. |
Connect your AI agent to Google NotebookLM. Add sources automatically, query your notebooks, generate branded slide decks, and keep your session alive without manual re-login.
Built on top of notebooklm-py by Teng Lin.
pip install "notebooklm-py[browser]"
The [browser] extra installs Playwright, needed for the one-time login. All queries run without a browser after that.
If pip is unavailable or the package is outdated, install from a specific GitHub release tag:
# Get the latest release tag
LATEST_TAG=$(curl -s https://api.github.com/repos/teng-lin/notebooklm-py/releases/latest | grep '"tag_name"' | cut -d'"' -f4)
pip install "git+https://github.com/teng-lin/notebooklm-py@${LATEST_TAG}"
Do NOT install from
git+https://github.com/teng-lin/notebooklm-pywithout a tag — the main branch may contain unstable code.
playwright install chromium
python scripts/nlm.py login
This opens a browser window. Sign into your Google account, wait until you see the NotebookLM homepage, then press ENTER in the terminal. Your session is saved to ~/.notebooklm/storage_state.json.
After this, your agent can access NotebookLM without any manual login.
python scripts/nlm.py list
You should see your notebooks listed.
All commands run through python scripts/nlm.py.
# List all notebooks
python scripts/nlm.py list
# Create a new notebook
python scripts/nlm.py create "My Research"
# Describe a notebook (AI summary of contents)
python scripts/nlm.py describe NOTEBOOK_ID
# Add a URL (articles, YouTube videos, etc.)
python scripts/nlm.py add-source --notebook-id NOTEBOOK_ID --url "https://example.com/article"
# Add a local file (PDF, markdown, txt, docx)
python scripts/nlm.py add-source --notebook-id NOTEBOOK_ID --file "/path/to/doc.pdf"
# Add raw text
python scripts/nlm.py add-source --notebook-id NOTEBOOK_ID --title "My Notes" --text "Content here..."
# List sources in a notebook
python scripts/nlm.py sources --notebook-id NOTEBOOK_ID
# Ask a question (set active notebook first, or pass --notebook-id)
python scripts/nlm.py ask "What are the main concepts?" --notebook-id NOTEBOOK_ID
# Add to local library with a name and description
python scripts/nlm.py library-add --notebook-id NOTEBOOK_ID --name "Claude Docs" --description "All Claude documentation"
# Set as the active (default) notebook
python scripts/nlm.py library-activate claude-docs
# List library
python scripts/nlm.py library-list
# Generate deep-dive audio (podcast style)
python scripts/nlm.py generate-audio --notebook-id NOTEBOOK_ID
# Generate a briefing doc
python scripts/nlm.py generate-report --notebook-id NOTEBOOK_ID
# Generate a study guide
python scripts/nlm.py generate-report --notebook-id NOTEBOOK_ID --format study_guide
# Generate a blog post
python scripts/nlm.py generate-report --notebook-id NOTEBOOK_ID --format blog_post
# List all generated artifacts (audio, reports, etc.)
python scripts/nlm.py artifacts --notebook-id NOTEBOOK_ID
Agent instruction: Before running any slide generation, always ask the user:
"What are your brand colors? I need:
- Primary color (main accent — e.g.
#FF6B2C)- Secondary color (supporting — e.g.
#FFBE2E)- Background color (e.g.
#000000for black,#1A1A2Efor dark navy)- Text color (e.g.
#F5F5F5for off-white)If you don't have hex codes, describe them and I'll pick the closest match."
Once you have the colors, substitute them into the slide prompt template below.
Use this as a Focus Prompt inside NotebookLM (Studio → Focus). The agent fills in the placeholders before sending.
Create a [NUMBER]-slide presenter deck for "[VIDEO TITLE]."
Design: Dark blackboard on [BACKGROUND_COLOR]. TITLES: bold slab serif (Rockwell or Roboto Slab), stamped/typeset, color [PRIMARY_COLOR]. Body text: handwritten chalk-style, color [TEXT_COLOR]. Each slide features one key glossy 3D object that floats above the chalk background. Chalk dashed connector lines link 3D elements to surrounding sketch labels. Every slide: dashed border in [PRIMARY_COLOR] + [CORNER_ICON] icon top-right corner. [PRIMARY_COLOR] PRIMARY, [SECONDARY_COLOR] SECONDARY, [TEXT_COLOR] text, [BACKGROUND_COLOR] background.
Slide 1: [SLIDE_1_DESCRIPTION]
Slide 2: [SLIDE_2_DESCRIPTION]
...
CRITICAL: Every slide — slab serif TITLE in [PRIMARY_COLOR] at top, dashed [PRIMARY_COLOR] border, [CORNER_ICON] icon top-right. Chalk body text. [BACKGROUND_COLOR] background. One 3D object per slide. [PRIMARY_COLOR] PRIMARY.
Placeholders to fill:
| Placeholder | What to fill |
|---|---|
[NUMBER] | How many slides |
[VIDEO TITLE] | The topic/title of the content |
[PRIMARY_COLOR] | User's primary brand color (hex) |
[SECONDARY_COLOR] | User's secondary brand color (hex) |
[BACKGROUND_COLOR] | Background color (hex) |
[TEXT_COLOR] | Text color (hex) |
[CORNER_ICON] | Icon that appears on every slide (e.g. lightning bolt, star, logo description) |
[SLIDE_N_DESCRIPTION] | Per-slide: what the slide covers, what 3D object appears, what labels surround it |
Each slide description should be ~150 characters. Be specific:
Slide 2: [TOPIC]. 3D [OBJECT] floating [POSITION]. Chalk labels: "[LABEL 1]," "[LABEL 2]," "[LABEL 3]." [PRIMARY_COLOR] dashed arrow pointing to [KEY ELEMENT].
3D object suggestions by topic:
Once filled in, run:
python scripts/nlm.py generate-report --notebook-id NOTEBOOK_ID --format custom --prompt "YOUR FILLED PROMPT HERE"
Or paste it directly into NotebookLM → Studio → Focus prompt.
Note: NotebookLM has a ~5,000 character limit on focus prompts. If your prompt is too long, shorten the per-slide descriptions.
Google session cookies expire after 7–30 days. There are two approaches:
When you get an auth error, just run:
python scripts/nlm.py login
Takes 30 seconds. Fine for occasional use.
scripts/refresh_auth.py silently refreshes your cookies using the persistent browser profile — no browser window, no manual steps. Run it every few days before cookies expire.
python scripts/refresh_auth.py # Refresh cookies
python scripts/refresh_auth.py --check # Just check if they're valid
To automate this, add a scheduled task or cron job:
# Cron example — refresh every 3 days at 5:30am
30 5 */3 * * python /path/to/scripts/refresh_auth.py
For Claude Code agent setups, add this to your agent's cron-registry.json:
{
"id": "notebooklm-auth-refresh",
"name": "NotebookLM cookie refresh (every 3 days)",
"cron": "30 5 */3 * *",
"prompt": "Run: python /path/to/scripts/refresh_auth.py — if it fails, alert the user to run notebooklm login manually.",
"enabled": true
}
How it works: Your first login saves a full browser profile to
~/.notebooklm/browser_profile/. Google keeps this session alive much longer than raw cookies because the browser handles token rotation automatically. The refresh script uses this profile headlessly to export fresh cookies — no human interaction needed.
Auth error / "Authentication expired"
Run python scripts/refresh_auth.py first. If that fails, run python scripts/nlm.py login to do a full re-login.
nlm command not found in terminal
Use python scripts/nlm.py instead. This is a Windows PATH issue with certain Python installations (common with Windows Store Python). The scripts work fine when called with python directly.
"No notebook specified"
Either pass --notebook-id YOUR_ID or set an active notebook first:
python scripts/nlm.py library-activate your-notebook-name
Slide generation times out NotebookLM can take 3–6 minutes to generate custom reports. If the command times out, check your artifacts list — the generation likely completed on NotebookLM's side:
python scripts/nlm.py artifacts --notebook-id NOTEBOOK_ID
Playwright / Chromium not found
Run playwright install chromium to install the browser.
Windows: "UnicodeEncodeError" on output
Set PYTHONUTF8=1 in your environment, or run $env:PYTHONUTF8="1" in PowerShell before running the script.