NotebookLM MCP Server
This repository provides a Model Context Protocol (MCP) server for NotebookLM. It allows AI assistants (like Claude, Antigravity, or others supporting MCP) to interact with your NotebookLM notebooks, sources, and conversations.
Features
- List Notebooks: View all your NotebookLM notebooks.
- Create Notebooks: Programmatically create new notebooks.
- Manage Sources: Add websites, Google Drive documents, or pasted text to your notebooks.
- Query Notebooks: Ask questions about your sources using the NotebookLM AI.
- Conversation History: Full support for follow-up questions and conversation context.
- Auto-Save Notes: Automatically save AI responses as notes in your notebooks.
Prerequisites
- Python 3.10 or higher.
- A Google Account with access to NotebookLM.
- An MCP-compatible client (e.g., Cursor, Claude Desktop).
Quick Start
1. Clone the repository
git clone https://github.com/YOUR_USERNAME/MCPNotebookLM.git
cd MCPNotebookLM
2. Set up the environment
Install dependencies:
pip install -r requirements.txt
Authenticate with NotebookLM:
notebooklm-mcp-auth
Follow the prompts to authorize the application. This will create a local auth.json file in ~/.notebooklm-mcp/.
3. Configure your MCP Client
For Cursor:
Copy
mcp_config.json.exampleto your Cursor config directory:- Linux:
~/.config/cursor/mcp.json - macOS:
~/Library/Application Support/Cursor/mcp.json - Windows:
%APPDATA%\Cursor\mcp.json
- Linux:
Edit the
commandfield with the absolute path tonotebooklm-mcp:{ "mcpServers": { "notebooklm": { "command": "/home/YOUR_USER/.local/bin/notebooklm-mcp", "args": [], "env": {} } } }Find the binary path:
which notebooklm-mcp # or ls ~/.local/bin/notebooklm-mcpRestart Cursor to apply the configuration.
Usage Examples
Basic Usage
Test your setup by listing notebooks:
python3 query_notebook_mcp.py
Or query a notebook directly:
python3 query_notebook_mcp.py <notebook_id> "Your question"
Auto-Save Notes Feature
The repository includes an automatic note-saving feature that saves all AI responses as notes in your notebooks. This is especially useful when working through MCP API, as responses aren't automatically saved in the web interface history.
Quick start:
from auto_save_notes import query_and_save
answer, source_id = query_and_save(
notebook_id="your-notebook-id",
question="What is Python?",
auto_save=True
)
See docs/AUTO_SAVE_NOTES.md for detailed documentation (if available locally).
Security Note
[!WARNING]Your authentication tokens are stored locally in
~/.notebooklm-mcp/auth.json. Never share this file or commit it to a public repository. The.gitignorein this repo is already configured to ignore this folder.
License
MIT