Which integrations are available for this server?

Provides automation capabilities for Google's NotebookLM service, enabling AI agents to send chat messages, retrieve streaming responses, manage notebooks, upload documents, and interact with NotebookLM's AI features through persistent browser sessions.

How do I use NotebookLM MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@NotebookLM MCP Server summarize the key points from my uploaded research paper" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

🚀 NotebookLM MCP

Professional MCP server for Google NotebookLM automation • Available on PyPI • Production Ready

Python 3.10+ DeepWiki Tests codecov License: MIT

✨ Key Features

🔥 FastMCP v2: Modern decorator-based MCP framework
⚡ UV Python Manager: Lightning-fast dependency management
🚀 Multiple Transports: STDIO, HTTP, SSE support
🎯 Type Safety: Full Pydantic validation
🔒 Persistent Auth: Automatic Google session management
📊 Rich CLI: Beautiful terminal interface with Taskfile automation
🐳 Production Ready: Docker support with monitoring

🏃‍♂️ Quick Start

🎯 For End Users (Recommended)

# Install UV (modern Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install NotebookLM MCP from PyPI
uv add notebooklm-mcp

# Initialize with your NotebookLM URL
uv run notebooklm-mcp init https://notebooklm.google.com/notebook/YOUR_NOTEBOOK_ID

What happens after

✅ Creates notebooklm-config.json with your settings
✅ Creates chrome_profile_notebooklm/ folder for persistent authentication
✅ Opens browser for one-time Google login (if needed)
✅ Saves session for future headless operation

# Start server (STDIO for MCP clients)
uv run notebooklm-mcp --config notebooklm-config.json server

# Start HTTP server for web testing
uv run notebooklm-mcp --config notebooklm-config.json server --transport http --port 8001

# Interactive chat mode
uv run notebooklm-mcp --config notebooklm-config.json chat  --message "Who are you ?"

👨‍💻 For Developers

If you're contributing to this project, check out our Taskfile for enhanced developer experience:

git clone https://github.com/khengyun/notebooklm-mcp.git
cd notebooklm-mcp

# Complete setup with development tools
task setup

# Show all available development tasks
task --list

🔧 Alternative Installation

If you prefer pip over UV:

# Install with pip
pip install notebooklm-mcp

# Initialize
notebooklm-mcp init https://notebooklm.google.com/notebook/YOUR_NOTEBOOK_ID

# Start server
notebooklm-mcp --config notebooklm-config.json server

� Project Structure After Init

After running init, your working directory will contain:

your-project/
├── notebooklm-config.json          # Configuration file
├── chrome_profile_notebooklm/      # Browser profile (persistent auth)
│   ├── Default/                    # Chrome profile data
│   ├── SingletonSocket             # Session files
│   └── ...                         # Other Chrome data
└── your-other-files

Key files:

notebooklm-config.json: Contains notebook ID, server settings, auth configuration
chrome_profile_notebooklm/: Stores Google authentication session (enables headless operation)

�🛠️ Available Tools

Tool	Description	Parameters
`healthcheck`	Server health status	None
`send_chat_message`	Send message to NotebookLM	`message: str`, `wait_for_response: bool`
`get_chat_response`	Get response with timeout	`timeout: int`
`chat_with_notebook`	Complete interaction	`message: str`, `notebook_id?: str`
`navigate_to_notebook`	Switch notebooks	`notebook_id: str`
`get_default_notebook`	Current notebook	None
`set_default_notebook`	Set default	`notebook_id: str`
`get_quick_response`	Instant response	None

👨‍💻 Developer Workflow

For contributors and advanced users who want enhanced productivity, we provide a comprehensive Taskfile with 20+ automation tasks:

# 📦 Dependency Management
task deps-add -- requests       # Add dependency
task deps-add-dev -- pytest     # Add dev dependency
task deps-remove -- requests    # Remove dependency
task deps-list                  # List dependencies
task deps-update                # Update all dependencies

# 🧪 Testing & Quality
task test                       # Run all tests
task test-quick                 # Quick validation test
task test-coverage              # Coverage analysis
task enforce-test               # MANDATORY after function changes
task lint                       # Run all linting
task format                     # Format code (Black + isort + Ruff)

# 🏗️ Build & Release
task build                      # Build package
task clean                      # Clean artifacts

# 🚀 Server Commands
task server-stdio              # STDIO server
task server-http               # HTTP server
task server-sse                # SSE server

# Show all available tasks
task --list

💡 Pro Tip: Install Task for the best developer experience: go install github.com/go-task/task/v3/cmd/task@latest

🌐 Transport Options

STDIO (Default)

task server-stdio
# For: LangGraph, CrewAI, AutoGen

HTTP

task server-http  
# Access: http://localhost:8001/mcp
# For: Web testing, REST APIs

SSE

task server-sse
# Access: http://localhost:8002/
# For: Real-time streaming

🧪 Testing & Development

HTTP Client Testing

from fastmcp import Client
from fastmcp.client.transports import StreamableHttpTransport

transport = StreamableHttpTransport(url="http://localhost:8001/mcp")
async with Client(transport) as client:
    tools = await client.list_tools()
    result = await client.call_tool("healthcheck", {})

Command Line Testing

# Test with curl
curl -X POST http://localhost:8001/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc": "2.0", "id": 1, "method": "tools/list", "params": {}}'

📊 Client Integration

LangGraph

from fastmcp import Client
from fastmcp.client.transports import StreamableHttpTransport

# HTTP transport
transport = StreamableHttpTransport(url="http://localhost:8001/mcp")
client = Client(transport)
tools = await client.list_tools()

CrewAI

from crewai_tools import BaseTool
from fastmcp import Client

class NotebookLMTool(BaseTool):
    name = "notebooklm"
    description = "Chat with NotebookLM"
    
    async def _arun(self, message: str):
        client = Client("http://localhost:8001/mcp")
        result = await client.call_tool("chat_with_notebook", {"message": message})
        return result

🔒 Authentication

Automatic Setup

# First time - opens browser for login
notebooklm-mcp init https://notebooklm.google.com/notebook/abc123

# Subsequent runs - uses saved session
notebooklm-mcp --config notebooklm-config.json server

Manual Setup

# Interactive browser login
notebooklm-mcp --config notebooklm-config.json server

# Check connection
notebooklm-mcp --config notebooklm-config.json test --notebook YOUR_NOTEBOOK_ID

🐳 Docker Deployment

Quick Start

# 1. Generate config + Chrome profile with guided login
uv run notebooklm-mcp init https://notebooklm.google.com/notebook/YOUR_NOTEBOOK_ID
# If you installed via pip, run: notebooklm-mcp init https://notebooklm.google.com/notebook/YOUR_NOTEBOOK_ID

# 2. Build the container image
docker build -t notebooklm-mcp .

# 3. Run the server with your mounted config/profile
docker run -d \
  --name notebooklm-mcp \
  --restart unless-stopped \
  -v $(pwd)/notebooklm-config.json:/app/notebooklm-config.json:ro \
  -v $(pwd)/chrome_profile_notebooklm:/app/chrome_profile_notebooklm \
  notebooklm-mcp:latest

With Compose

version: '3.8'
services:
  notebooklm-mcp:
    image: notebooklm-mcp:latest
    build: .
    restart: unless-stopped
    volumes:
      - ./notebooklm-config.json:/app/notebooklm-config.json:ro
      - ./chrome_profile_notebooklm:/app/chrome_profile_notebooklm

Start the stack with docker compose up -d after running the init command once so that notebooklm-config.json and chrome_profile_notebooklm/ exist. The server runs in STDIO mode by default; uncomment the HTTP/SSE ports in docker-compose.yml if your client requires them.

⚙️ Configuration

Config File (`notebooklm-config.json`)

{
  "default_notebook_id": "your-notebook-id",
  "headless": true,
  "timeout": 30,
  "auth": {
    "profile_dir": "./chrome_profile_notebooklm"
  },
  "debug": false
}

Environment Variables

export NOTEBOOKLM_NOTEBOOK_ID="your-notebook-id"
export NOTEBOOKLM_HEADLESS=true
export NOTEBOOKLM_DEBUG=false

🚀 Performance

FastMCP v2 Benefits

⚡ 5x faster tool registration with decorators
📋 Auto-generated schemas from Python type hints
🔒 Built-in validation with Pydantic
🧪 Better testing and debugging capabilities
📊 Type safety throughout the stack

Benchmarks

Feature	Traditional MCP	FastMCP v2
Tool registration	Manual schema	Auto-generated
Type validation	Manual	Automatic
Error handling	Basic	Enhanced
Development speed	Standard	5x faster
HTTP support	Limited	Full

🛠️ Development

Setup

git clone https://github.com/khengyun/notebooklm-mcp
cd notebooklm-mcp

# With UV (recommended)
uv sync --all-groups

# Or with pip
pip install -e ".[dev]"

Testing

# Run tests with UV
uv run pytest

# With coverage
uv run pytest --cov=notebooklm_mcp

# Integration tests  
uv run pytest tests/test_integration.py

# Or use Taskfile for development
task test
task test-coverage

Code Quality

# Format code with UV
uv run black src/ tests/
uv run ruff check src/ tests/

# Type checking
uv run mypy src/

# Or use Taskfile shortcuts
task format
task lint

📚 Documentation

Quick Setup Guide - Get started in 2 minutes
HTTP Server Guide - Web testing & integration
FastMCP v2 Guide - Modern MCP features
Docker Deployment - Production setup
API Reference - Complete tool documentation

FastMCP - Modern MCP framework
MCP Specification - Official MCP spec
NotebookLM - Google's AI notebook

📄 License

MIT License - see LICENSE file for details.

🆘 Support

Issues: GitHub Issues
Discussions: GitHub Discussions
Documentation: Read the Docs

Built with ❤️ using FastMCP v2 - Modern MCP development made simple!