NotebookLM MCP Server (Security Hardened)

🏆 The World's Most Advanced NotebookLM MCP Server

Zero-hallucination answers • Gemini Deep Research • 14 Security Layers • Enterprise Compliance

What's New 2026 • Deep Research • Document API • Create Notebooks • Security • Install

The only NotebookLM MCP with enterprise-grade security, post-quantum encryption, and full Gemini API integration.

Security-hardened fork of PleasePrompto/notebooklm-mcp • Maintained by Pantheon Security

⚡ TL;DR — What You Get

• 🔍 Query your NotebookLM notebooks — source-grounded, zero-hallucination answers

• 📚 Create & manage notebooks programmatically — no manual clicking

• 🎙️ Generate audio overviews — podcast-style summaries of your docs

• 🔬 Gemini Deep Research — comprehensive multi-source research (optional API)

• 📄 Document API — upload & query PDFs without browser (optional API)

• 🔐 14 security layers — post-quantum encryption, audit logs, secrets scanning

• ✅ Enterprise compliance — GDPR, SOC2, CSSF ready

• 💡 No API key required — core features work with just browser auth

🚀 What's New in 2026

Latest: v2026.1.8 — Updated dependencies, post-quantum crypto improvements

Why Choose This MCP?

Core NotebookLM (No API Key Required)

Gemini API (Optional - Requires GEMINI_API_KEY)

Webhooks & Integrations

Enterprise Compliance (16 additional tools)

See Compliance Documentation for full list.

Gemini Deep Research (v1.8.0)

The most powerful research capability for AI agents — now in your MCP toolkit.

v1.8.0 introduces the Gemini Interactions API as a stable, API-based research backend alongside browser automation. This gives your agents access to Google's state-of-the-art Deep Research agent.

Why This Matters

New Tools

deep_research — Comprehensive Research Agent

• Runs Google's Deep Research agent (same as Gemini Advanced)

• Takes 1-5 minutes for comprehensive, web-grounded analysis

• Returns structured answers with citations and sources

• Perfect for complex topics requiring multi-source synthesis

gemini_query — Fast Grounded Queries

• Google Search grounding — Current information, not just training data

• Code execution — Run calculations, data analysis

• URL context — Analyze web pages on demand

• Models: gemini-2.5-flash (fast), gemini-2.5-pro (powerful), gemini-3-flash-preview (latest)

get_research_status — Background Task Monitoring

Run deep research in the background and check progress:

Hybrid Architecture

💡 Gemini API is completely optional! All core NotebookLM features (ask_question, notebooks, sessions, audio) work via browser automation with no API key required. The Gemini tools below are bonus features for users who want direct API access.

Gemini Configuration (Optional)

When to Use Which

📄 Document API (v1.9.0)

Upload and query documents directly via Gemini API — no browser automation needed.

v1.9.0 introduces the Gemini Files API for fast, reliable document analysis. Upload PDFs, analyze them instantly, and delete when done.

Why This Matters

New Tools

upload_document — Fast Document Upload

Upload any document to Gemini for instant querying:

• Supported: PDF (50MB, 1000 pages), TXT, MD, HTML, CSV, JSON, DOCX, images, audio, video

• 48-hour retention — files auto-expire, or delete manually

• Returns a file ID for querying

query_document — Ask Questions About Documents

• Full document understanding (text, tables, charts, diagrams)

• Multi-document queries (compare multiple files)

• Fast API response (no browser wait)

list_documents — See All Uploaded Files

Shows file names, sizes, MIME types, and expiration times.

delete_document — Clean Up Sensitive Files

Immediately remove files (don't wait for 48h expiration).

Workflow Example

Auto-Chunking for Large PDFs (v1.10.0)

No file size limits — PDFs of any size are automatically handled.

When you upload a PDF that exceeds Gemini's limits (50MB or 1000 pages), the system automatically:

1. Detects the oversized PDF

2. Splits it into optimal chunks (500 pages each)

3. Uploads all chunks in parallel

4. Returns chunk metadata for querying

query_chunked_document — Query All Chunks at Once

For chunked documents, use this tool to query all parts and get an aggregated answer:

When to Use Document API vs NotebookLM

Programmatic Notebook Creation (v1.7.0+)

Create NotebookLM notebooks entirely from code — no manual clicks required.

Most MCP servers can only read from NotebookLM. This one can create notebooks, add sources, and generate audio — all programmatically.

create_notebook — Build Notebooks Instantly

Create a complete notebook with multiple sources in one command:

Supported source types:

• URL — Web pages, documentation, articles

• File — PDF, DOCX, TXT, and more

• Text — Raw text, code snippets, notes

batch_create_notebooks — Scale Up

Create up to 10 notebooks in a single operation:

Perfect for:

• Setting up project documentation libraries

• Onboarding new team members with curated knowledge bases

• Creating topic-specific research notebooks in bulk

manage_sources — Dynamic Source Management

Add or remove sources from existing notebooks:

generate_audio — Audio Overview Creation

Generate NotebookLM's famous "Audio Overview" podcasts programmatically:

sync_notebook — Keep Sources Updated

Sync notebook sources from a local directory:

Why This Matters

Your agent can now build entire knowledge bases autonomously.

📊 Query History & Chat Extraction (v2026.1.0)

Track your research and recover conversations from NotebookLM notebooks.

get_query_history — Review Past Research (v1.10.8)

All queries made through the MCP are automatically logged for review:

• Automatic logging — every Q&A pair saved with metadata

• Search — find specific topics across all queries

• Filter — by notebook, session, or date

• Quota tracking — see query counts and timing

get_notebook_chat_history — Extract Browser Conversations (v2026.1.0)

Extract conversation history directly from a NotebookLM notebook's chat UI with context management to avoid overwhelming your AI context window:

Quick audit (preview mode):

Returns message counts without content — test the water before extracting.

Export to file (avoids context overflow):

Dumps full history to disk instead of returning to context.

Paginate through history:

Page through large histories without loading everything at once.

Returns:

Use cases:

• Recover conversations made directly in the NotebookLM browser (not tracked by MCP)

• Audit research — see what queries were made in a notebook

• Resume context — pick up where a previous session left off

• Quota reconciliation — understand why quota seems off

Why This Fork?

The original NotebookLM MCP is excellent for productivity — but MCP servers handle sensitive data:

• Browser sessions with Google authentication

• Cookies and tokens stored on disk

• Query history that may contain proprietary information

This fork adds 14 security hardening layers to protect that data.

Security Features

Post-Quantum Ready

Traditional encryption (RSA, ECDH) will be broken by quantum computers. This fork uses hybrid encryption:

• ML-KEM-768: NIST-standardized post-quantum key encapsulation

• ChaCha20-Poly1305: Modern stream cipher (immune to timing attacks)

Even if one algorithm is broken, the other remains secure.

Cross-Platform Support

Full native support for all major operating systems:

All sensitive files (encryption keys, auth tokens, audit logs) are automatically protected with owner-only permissions on every platform.

Enterprise Compliance (v1.6.0+)

Full compliance support for regulated industries:

Compliance Tools (16 MCP tools)

See COMPLIANCE-SPEC.md for full documentation.

Installation

What Works Out of the Box (No API Key)

All core NotebookLM features work immediately with just browser authentication:

Optional: Add GEMINI_API_KEY for bonus features like deep_research, gemini_query, and upload_document.

Claude Code

With Authentication + Gemini (Recommended)

Codex

Add to ~/.cursor/mcp.json:

Add to ~/.gemini/antigravity/mcp_config.json (macOS/Linux) or %USERPROFILE%\.gemini\antigravity\mcp_config.json (Windows):

With optional env vars:

Note: Antigravity does NOT support ${workspaceFolder} variables. Use absolute paths.

Add to ~/.config/opencode/opencode.json (global) or opencode.json in project root:

Note: OpenCode uses "mcp" (not "mcpServers") and "command" is an array.

Add to ~/.codeium/windsurf/mcp_config.json:

Add to your VS Code settings.json:

Most MCP clients use this standard format:

Common config locations:

Quick Start

1. Install (see above)

2. Authenticate

Chrome opens → sign in with Google

3. Add your notebook

Go to notebooklm.google.com → Create notebook → Upload docs → Share link

4. Use it

5. Try Deep Research (NEW!)

Complete Tool Reference

Research Tools

Notebook Management

Source Management (v1.7.0+)

Session & System

Compliance (v1.6.0+)

16 compliance tools for GDPR, SOC2, and CSSF requirements.

What Gets Protected

Configuration

All security features are enabled by default. Override via environment variables:

Multi-Session Mode

Run multiple Claude Code sessions simultaneously with isolated browser profiles:

How it works:

• Each session gets its own Chrome profile (no lock conflicts)

• Isolated profiles clone from the authenticated base profile

• Auth coordination ensures cloning waits for any in-progress authentication

See SECURITY.md for complete configuration reference.

Security Scanning

Run MEDUSA security scanner:

Or integrate in CI/CD:

Comparison

vs Other NotebookLM MCPs

Security & Compliance (Unique to This Fork)

Bottom line: If you need more than basic queries, or care about security, there's only one choice.

Version History

Reporting Vulnerabilities

Found a security issue? Do not open a public GitHub issue.

Email: support@pantheonsecurity.io

Credits

• Original MCP Server: Gérôme Dexheimer — notebooklm-mcp

• Security Hardening: Pantheon Security

• Post-Quantum Crypto: @noble/post-quantum

• Gemini API: Google AI

License

MIT — Same as original.

Security hardened with 🔒 by

Powered by Google Gemini 🚀

Full Security Documentation • Compliance Guide • Report Vulnerability