NotebookLM MCP Ultimate

44 MCP tools for AI-powered research via Google NotebookLM and Gemini 2.5

Installation • Quick Start • 44 Tools • Original Project

The Problem

When you tell Claude Code or Cursor to "search through my local documentation", here's what happens:

• Massive token consumption: Searching through documentation means reading multiple files repeatedly
• Inaccurate retrieval: Searches for keywords, misses context and connections between docs
• Hallucinations: When it can't find something, it invents plausible-sounding APIs
• Expensive & slow: Each question requires re-reading multiple files

The Solution

Let your local agents chat directly with NotebookLM — Google's zero-hallucination knowledge base powered by Gemini 2.5 that provides intelligent, synthesized answers from your docs.

Your Task → Local Agent asks NotebookLM → Gemini synthesizes answer → Agent writes correct code

The real advantage: No more manual copy-paste between NotebookLM and your editor. Your agent asks NotebookLM directly and gets answers straight back in the CLI. It builds deep understanding through automatic follow-ups — Claude asks multiple questions in sequence, each building on the last, getting specific implementation details, edge cases, and best practices. You can save NotebookLM links to your local library with tags and descriptions, and Claude automatically selects the relevant notebook based on your current task.

Why NotebookLM, Not Local RAG?

| Approach | Token Cost | Setup Time | Hallucinations | Answer Quality | |----------|------------|------------|----------------|----------------| | Feed docs to Claude | 🔴 Very high (multiple file reads) | Instant | Yes - fills gaps | Variable retrieval | | Web search | 🟡 Medium | Instant | High - unreliable sources | Hit or miss | | Local RAG | 🟡 Medium-High | Hours (embeddings, chunking) | Medium - retrieval gaps | Depends on setup | | NotebookLM MCP | 🟢 Minimal | 5 minutes | Zero - refuses if unknown | Expert synthesis |

What Makes NotebookLM Superior?

1. Pre-processed by Gemini: Upload docs once, get instant expert knowledge
2. Natural language Q&A: Not just retrieval — actual understanding and synthesis
3. Multi-source correlation: Connects information across 50+ documents
4. Citation-backed: Every answer includes source references
5. No infrastructure: No vector DBs, embeddings, or chunking strategies needed

Prerequisites

• Node.js >= 18 (download)
• A Google account with access to NotebookLM

Installation

Claude Code

claude mcp add notebooklm npx notebooklm-mcp-ultimate@latest

Codex

codex mcp add notebooklm -- npx notebooklm-mcp-ultimate@latest

gemini mcp add notebooklm npx notebooklm-mcp-ultimate@latest

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "notebooklm": {
      "command": "npx",
      "args": ["-y", "notebooklm-mcp-ultimate@latest"]
    }
  }
}

amp mcp add notebooklm -- npx notebooklm-mcp-ultimate@latest

code --add-mcp '{"name":"notebooklm","command":"npx","args":["notebooklm-mcp-ultimate@latest"]}'

Generic MCP config:

{
  "mcpServers": {
    "notebooklm": {
      "command": "npx",
      "args": ["notebooklm-mcp-ultimate@latest"]
    }
  }
}

Quick Start

1. Install the MCP server (see Installation above)

2. Authenticate (one-time)

Say in your chat (Claude/Codex):

"Log me in to NotebookLM"

A Chrome window opens → log in with Google

Headless/CI/CD? Copy ~/.local/share/notebooklm-mcp/browser_state/state.json and set:

export GOOGLE_AUTH_COOKIES_PATH=/path/to/state.json

See Headless Auth docs for details.

3. Create your knowledge base

Go to notebooklm.google.com → Create notebook → Upload your docs:

• 📄 PDFs, Google Docs, markdown files
• 🔗 Websites, GitHub repos
• 🎥 YouTube videos
• 📚 Multiple sources per notebook

Share: ⚙️ Share → Anyone with link → Copy

4. Let Claude use it

"I'm building with [library]. Here's my NotebookLM: [link]"

That's it. Claude now asks NotebookLM whatever it needs, building expertise before writing code.

Real-World Example

Building an n8n Workflow Without Hallucinations

Challenge: n8n's API is new — Claude hallucinates node names and functions.

Solution:

1. Downloaded complete n8n documentation → merged into manageable chunks
2. Uploaded to NotebookLM
3. Told Claude: "Build me a Gmail spam filter workflow. Use this NotebookLM: [link]"

Watch the AI-to-AI conversation:

Claude → "How does Gmail integration work in n8n?"
NotebookLM → "Use Gmail Trigger with polling, or Gmail node with Get Many..."

Claude → "How to decode base64 email body?"
NotebookLM → "Body is base64url encoded in payload.parts, use Function node..."

Claude → "How to parse OpenAI response as JSON?"
NotebookLM → "Set responseFormat to json, use {{ $json.spam }} in IF node..."

Claude → "What about error handling if the API fails?"
NotebookLM → "Use Error Trigger node with Continue On Fail enabled..."

Claude → ✅ "Here's your complete workflow JSON..."

Result: Perfect workflow on first try. No debugging hallucinated APIs.

Core Features

Zero Hallucinations

NotebookLM refuses to answer if information isn't in your docs. No invented APIs.

Autonomous Research

Claude asks follow-up questions automatically, building complete understanding before coding.

Smart Library Management

Save NotebookLM links with tags and descriptions. Claude auto-selects the right notebook for your task.

"Add [link] to library tagged 'frontend, react, components'"

Deep, Iterative Research

• Claude automatically asks follow-up questions to build complete understanding
• Each answer triggers deeper questions until Claude has all the details
• Example: For n8n workflow, Claude asked multiple sequential questions about Gmail integration, error handling, and data transformation

Cross-Tool Sharing

Set up once, use everywhere. Claude Code, Codex, Cursor — all share the same library.

Deep Cleanup Tool

Fresh start anytime. Scans entire system for NotebookLM data with categorized preview.

Tool Categories

44 tools across 9 categories:

| Category | Count | Tools | |----------|-------|-------| | System Management | 4 | get_health, setup_auth, re_auth, cleanup_data | | Session Management | 3 | list_sessions, close_session, reset_session | | Notebook Management | 8 | add_notebook, list_notebooks, get_notebook, select_notebook, update_notebook, remove_notebook, search_notebooks, get_library_stats | | Notebook CRUD | 4 | create_notebook_remote, rename_notebook_remote, delete_notebook_remote, add_file_source | | Q&A | 1 | ask_question | | Content Generation | 9 | generate_faq, generate_briefing, generate_timeline, generate_outline, generate_study_guide, generate_flashcards, generate_quiz, generate_mindmap, suggest_questions | | Audio Studio | 5 | get_audio_status, create_audio, update_audio, delete_audio, download_audio | | Source Management | 7 | list_sources, add_url_source, add_text_source, add_youtube_source, add_drive_source, delete_source, summarize_source | | Research | 3 | discover_sources, import_source, research_topic |

See the Tool Categories section for details.

Tool Profiles

Reduce token usage by loading only the tools you need:

| Profile | Tools | Use Case | |---------|-------|----------| | minimal | 5 | Query-only | | standard | 10 | + Library management | | full | 44 | All tools |

npx notebooklm-mcp config set profile minimal   # or standard / full
npx notebooklm-mcp config set disabled-tools "cleanup_data,re_auth"

See .env.example for all available options.

Architecture

graph LR
    A[Your Task] --> B[Claude/Codex]
    B --> C[MCP Server]
    C --> D[Chrome Automation]
    D --> E[NotebookLM]
    E --> F[Gemini 2.5]
    F --> G[Your Docs]
    G --> F
    F --> E
    E --> D
    D --> C
    C --> B
    B --> H[Accurate Code]

Common Commands

| Intent | Say | Result | |--------|-----|--------| | Authenticate | "Open NotebookLM auth setup" or "Log me in to NotebookLM" | Chrome opens for login | | Add notebook | "Add [link] to library" | Saves notebook with metadata | | List notebooks | "Show our notebooks" | Lists all saved notebooks | | Research first | "Research this in NotebookLM before coding" | Multi-question session | | Select notebook | "Use the React notebook" | Sets active notebook | | Update notebook | "Update notebook tags" | Modify metadata | | Remove notebook | "Remove [notebook] from library" | Deletes from library | | View browser | "Show me the browser" | Watch live NotebookLM chat | | Fix auth | "Repair NotebookLM authentication" | Clears and re-authenticates | | Switch account | "Re-authenticate with different Google account" | Changes account | | Clean restart | "Run NotebookLM cleanup" | Removes all data for fresh start | | Keep library | "Cleanup but keep my library" | Preserves notebooks | | Delete all data | "Delete all NotebookLM data" | Complete removal |

Comparison to Alternatives

vs. Downloading docs locally

• You: Download docs → Claude: "search through these files"
• Problem: Claude reads thousands of files → massive token usage, often misses connections
• NotebookLM: Pre-indexed by Gemini, semantic understanding across all docs

vs. Web search

• You: "Research X online"
• Problem: Outdated info, hallucinated examples, unreliable sources
• NotebookLM: Only your trusted docs, always current, with citations

vs. Local RAG setup

• You: Set up embeddings, vector DB, chunking strategy, retrieval pipeline
• Problem: Hours of setup, tuning retrieval, still gets "creative" with gaps
• NotebookLM: Upload docs → done. Google handles everything.

FAQ

Is it really zero hallucinations? Yes. NotebookLM is specifically designed to only answer from uploaded sources. If it doesn't know, it says so.

What about rate limits? Free tier has daily query limits per Google account. Quick account switching supported for continued research.

How secure is this? Chrome runs locally. Your credentials never leave your machine. Use a dedicated Google account if concerned.

Can I see what's happening? Yes! Say "Show me the browser" to watch the live NotebookLM conversation.

What makes this better than Claude's built-in knowledge? Your docs are always current. No training cutoff. No hallucinations. Perfect for new libraries, internal APIs, or fast-moving projects.

Documentation

• CHANGELOG — Version history and release notes
• CONTRIBUTING — Development setup and guidelines
• .env.example — All 30+ configuration options

The Bottom Line

Without NotebookLM MCP: Write code → Find it's wrong → Debug hallucinated APIs → Repeat

With NotebookLM MCP: Claude researches first → Writes correct code → Ship faster

Stop debugging hallucinations. Start shipping accurate code.

# Get started in 30 seconds
claude mcp add notebooklm npx notebooklm-mcp-ultimate@latest

Disclaimer

This tool automates browser interactions with NotebookLM to make your workflow more efficient. However, a few friendly reminders:

About browser automation: While I've built in humanization features (realistic typing speeds, natural delays, mouse movements) to make the automation behave more naturally, I can't guarantee Google won't detect or flag automated usage. I recommend using a dedicated Google account for automation rather than your primary account—think of it like web scraping: probably fine, but better safe than sorry!

About CLI tools and AI agents: CLI tools like Claude Code, Codex, and similar AI-powered assistants are incredibly powerful, but they can make mistakes. Please use them with care and awareness:

• Always review changes before committing or deploying
• Test in safe environments first
• Keep backups of important work
• Remember: AI agents are assistants, not infallible oracles

I built this tool for myself because I was tired of the copy-paste dance between NotebookLM and my editor. I'm sharing it in the hope it helps others too, but I can't take responsibility for any issues, data loss, or account problems that might occur. Use at your own discretion and judgment.

That said, if you run into problems or have questions, feel free to open an issue on GitHub. I'm happy to help troubleshoot!

Contributing

We welcome contributions! See CONTRIBUTING.md for development setup and guidelines.

Found a bug? Have a feature idea? Open an issue.

Security

To report a vulnerability, please use GitHub Security Advisories. See SECURITY.md for details.

Code of Conduct

This project follows the Contributor Covenant. Please be respectful in all interactions.

Acknowledgements

This project builds on the work of others:

• notebooklm-mcp by Gérôme Dexheimer — the original MCP server this project was forked from

License

MIT — Use freely in your projects.

Built with frustration about hallucinated APIs, powered by Google's NotebookLM

⭐ Star on GitHub if this saves you debugging time!