NotebookLM MCP Server

Local setup required. This server has to be cloned and prepared on your machine before you register it in Claude Code.
1

Set the server up locally

Run this once to clone and prepare the server before adding it to Claude Code.

Run in terminal
pip install .
2

Register it in Claude Code

After the local setup is done, run this command to point Claude Code at the built server.

Run in terminal
claude mcp add notebooklm-mcp-a510 -- node "<FULL_PATH_TO_NOTEBOOKLM_MCP>/dist/index.js"

Replace <FULL_PATH_TO_NOTEBOOKLM_MCP>/dist/index.js with the actual folder you prepared in step 1.

README.md

Query and interact with Google NotebookLM notebooks via AI agents

NotebookLM MCP Server

This is an unofficial Model Context Protocol (MCP) server for Google NotebookLM, allowing AI agents and assistants (like Google Antigravity, Claude Code, Cursor, etc.) to query your Notebooks and retrieve citation-backed answers.

Prerequisites

  • Python 3.10+
  • A Google NotebookLM session cookie.

Installation

  1. Clone this repository.
  2. Initialize and activate a virtual environment:
    python3 -m venv .venv
    source .venv/bin/activate
    
  3. Install dependencies:
    pip install .
    

Configuration

You need to authenticate the unofficial API so it can access your Notebooks.

  1. Authenticate via Playwright: Run the interactive login command provided by notebooklm-py:
    uv run notebooklm login
    # or if using a standard python venv:
    notebooklm login
    
    This will open a Chromium browser window where you can log in to your Google Account. Once logged in and on the NotebookLM page, close the browser. The session will be saved locally.

Usage

Start the MCP server over stdio using the command-line entry point:

uv run python -m mcp_notebooklm
# or if using standard python venv:
python -m mcp_notebooklm

Server Tools

This server exposes the following MCP tools:

  • list_notebooks: Lists all your Notebooks (returns their IDs and Titles).
  • get_notebook_sources: Retrieves the data sources for a specific notebook.
  • ask_notebook: Passes a natural language query to a specific notebook and returns the AI-generated answer.
  • select_notebook: Selects a notebook by ID and creates a local directory for it.
  • create_note: Creates a new text note in the specified notebook.
  • download_notes: Downloads all notes from a specific notebook into a local subfolder.
  • generate_audio: Generates an Audio Overview (podcast) for a notebook.
  • generate_video: Generates a Video Overview for a notebook.
  • generate_slides: Generates a Slide Deck for a notebook.
  • generate_infographic: Generates an Infographic for a notebook.
  • generate_report: Generates a Report (Briefing Doc, Study Guide, Blog Post, Custom) for a notebook.

Using with Claude Desktop or Antigravity

Add this to your MCP settings configuration (mcp.json or equivalent):

{
  "mcpServers": {
    "notebooklm": {
      "command": "/path/to/your/virtualenv/bin/python",
      "args": [
        "-m",
        "mcp_notebooklm"
      ],
      "cwd": "/path/to/this/repo"
    }
  }
}

Tools (11)

list_notebooksLists all your Notebooks including their IDs and Titles.
get_notebook_sourcesRetrieves the data sources for a specific notebook.
ask_notebookPasses a natural language query to a specific notebook and returns the AI-generated answer.
select_notebookSelects a notebook by ID and creates a local directory for it.
create_noteCreates a new text note in the specified notebook.
download_notesDownloads all notes from a specific notebook into a local subfolder.
generate_audioGenerates an Audio Overview (podcast) for a notebook.
generate_videoGenerates a Video Overview for a notebook.
generate_slidesGenerates a Slide Deck for a notebook.
generate_infographicGenerates an Infographic for a notebook.
generate_reportGenerates a Report (Briefing Doc, Study Guide, Blog Post, Custom) for a notebook.

Configuration

claude_desktop_config.json
{"mcpServers": {"notebooklm": {"command": "/path/to/your/virtualenv/bin/python", "args": ["-m", "mcp_notebooklm"], "cwd": "/path/to/this/repo"}}}

Try it

List all my available notebooks and their IDs.
Ask my 'Project Research' notebook to summarize the key findings from its sources.
Generate an audio podcast overview for the notebook with ID 12345.
Download all notes from my 'Meeting Minutes' notebook to my local machine.
Create a study guide report for the notebook titled 'Advanced Physics'.

Frequently Asked Questions

What are the key features of NotebookLM MCP Server?

Retrieve citation-backed answers from NotebookLM sources. List and manage notebook content via natural language. Generate multimedia overviews including audio, video, and slides. Export notes to local storage. Create new notes directly within existing notebooks.

What can I use NotebookLM MCP Server for?

Researchers querying large document collections for specific citations. Students generating study guides and infographics from course materials. Professionals creating audio summaries of meeting notes for on-the-go listening. Content creators drafting blog posts based on existing research notebooks.

How do I install NotebookLM MCP Server?

Install NotebookLM MCP Server by running: pip install .

What MCP clients work with NotebookLM MCP Server?

NotebookLM MCP Server works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep NotebookLM MCP Server docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare