notebooklm-mcp: Instructions file for Gemini CLI

GEMINI.md

notebooklm-mcp GEMINI.md is an instructions file for Gemini CLI from Morfeu333/notebooklm-mcp. It costs 914 tokens per session, scanned A, original, MIT.

A set of project instructions for a command-line tool that connects AI agents to NotebookLM. NotebookLM is Google's app for asking questions about notebooks and their source materials.

In plain words
What is it for?
Use it when setting up, developing, authenticating, or running the NotebookLM MCP server with Python and Google Chrome.
Why use it?
It gives developers the project setup, authentication, environment, and installation information needed to work on the server.

Instructions file for Gemini CLI

Written for Gemini CLI: the file is GEMINI.md. Also seen: mentions CLAUDE.md; mentions Gemini CLI.

This is Morfeu333/notebooklm-mcp's own configuration. It tells Gemini CLI how to work on notebooklm-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything notebooklm-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Morfeu333/notebooklm-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Morfeu333/notebooklm-mcp/main/GEMINI.md
Clone the repo
git clone --depth 1 https://github.com/Morfeu333/notebooklm-mcp

Made for: Gemini CLI.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for notebooklm-mcp GEMINI.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/morfeu333/notebooklm-mcp/gemini-md.svg)](https://agentmods.dev/instructions/morfeu333/notebooklm-mcp/gemini-md)
Your own site
<a href="https://agentmods.dev/instructions/morfeu333/notebooklm-mcp/gemini-md"><img src="https://agentmods.dev/badge/instructions/morfeu333/notebooklm-mcp/gemini-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 914 This file is loaded in full into every session.
When invoked 914 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00914 $0.00914
Opus 5 $0.00457 $0.00457
Sonnet 5 $0.00183 $0.00183
Haiku 4.5 $0.00091 $0.00091

Measured 6d ago against content hash 007eb9612bdb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

notebooklm-mcp GEMINI.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

GEMINI.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GEMINI.md

Project Overview

NotebookLM MCP Server

This project implements a Model Context Protocol (MCP) server that provides programmatic access to NotebookLM. It allows AI agents and developers to interact with NotebookLM notebooks, sources, and query capabilities.

Tested with personal/free tier accounts. May work with Google Workspace accounts but has not been tested. This project relies on internal APIs (batchexecute RPCs).

Environment & Setup

The project uses uv for dependency management and tool installation.

Prerequisites

  • Python 3.11+
  • uv (Universal Python Package Manager)
  • Google Chrome (for automated authentication)

Installation

From PyPI (Recommended):

uv tool install notebooklm-mcp-server
# or: pip install notebooklm-mcp-server

From Source (Development):

git clone https://github.com/YOUR_USERNAME/notebooklm-mcp.git
cd notebooklm-mcp
uv tool install .

Authentication

Preferred: Run the automated authentication CLI:

notebooklm-mcp-auth

This launches Chrome, you log in, and cookies are extracted automatically. Your login is saved to a Chrome profile for future use.

Auto-refresh (v0.1.9+): The server now automatically handles token expiration:

  1. Refreshes CSRF tokens on expiry (immediate)
  2. Reloads cookies from disk if updated externally
  3. Runs headless Chrome auth if profile has saved login

If headless auth fails (Google login fully expired), you'll see a message to run notebooklm-mcp-auth again.

Explicit refresh (MCP tool):

refresh_auth()  # Reload tokens from disk or run headless auth

Fallback: Manual extraction (if CLI fails) If the automated tool doesn't work, extract cookies via Chrome DevTools:

  1. Open Chrome DevTools on notebooklm.google.com
  2. Go to Network tab, find a batchexecute request
  3. Copy the Cookie header and call save_auth_tokens(cookies=...)

Environment variable (advanced):

export NOTEBOOKLM_COOKIES="SID=xxx; HSID=xxx; SSID=xxx; ..."

Read the full file on GitHub · 121 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 121 lines · 914 tokens per session scan A 007eb9612bdb

Subscribe to this mod's changes

notebooklm-mcp GEMINI.md is an instructions file published in the GitHub repository Morfeu333/notebooklm-mcp (1 stars, last pushed 6mo ago), licensed MIT. It adds 914 tokens to every session, about $0.0046 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other instructions, from other repositories

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens