Provides integration with Google's NotebookLM service, enabling AI agents to authenticate with Google accounts, manage notebook libraries, ask questions against uploaded documents, and receive grounded responses with citations from NotebookLM's research capabilities.
NotebookLM MCP Server
Let your CLI agents (Claude, Cursor, Codex...) chat directly with NotebookLM for zero-hallucination answers based on your own notebooks
Installation • Quick Start • Why NotebookLM • Examples • Claude Code Skill • Documentation
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.
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?
Pre-processed by Gemini: Upload docs once, get instant expert knowledge
Natural language Q&A: Not just retrieval — actual understanding and synthesis
Multi-source correlation: Connects information across 50+ documents
Citation-backed: Every answer includes source references
No infrastructure: No vector DBs, embeddings, or chunking strategies needed
Installation
Claude Code
Codex
Add to ~/.cursor/mcp.json:
Generic MCP config:
Alternative: Claude Code Skill
Prefer Claude Code Skills over MCP? This server is now also available as a native Claude Code Skill with a simpler setup:
NotebookLM Claude Code Skill - Clone to ~/.claude/skills and start using immediately
Key differences:
MCP Server (this repo): Persistent sessions, works with Claude Code, Codex, Cursor, and other MCP clients
Claude Code Skill: Simpler setup, Python-based, stateless queries, works only with local Claude Code
Both use the same browser automation technology and provide zero-hallucination answers from your NotebookLM notebooks.
Quick Start
1. Install the MCP server (see Installation above)
2. Authenticate (one-time)
Say in your chat (Claude/Codex):
A Chrome window opens → log in with Google
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
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:
Downloaded complete n8n documentation → merged into manageable chunks
Uploaded to NotebookLM
Told Claude: "Build me a Gmail spam filter workflow. Use this NotebookLM: [link]"
Watch the AI-to-AI conversation:
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.
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 Profiles
Reduce token usage by loading only the tools you need. Each tool consumes context tokens — fewer tools = faster responses and lower costs.
Available Profiles
Profile | Tools | Use Case |
minimal | 5 | Query-only:
,
,
,
,
|
standard | 10 | + Library management:
,
,
,
,
|
full | 16 | All tools including
,
,
,
,
,
|
Configure via CLI
Configure via Environment Variables
Settings are saved to ~/.config/notebooklm-mcp/settings.json and persist across sessions. Environment variables override file settings.
Architecture
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.
Advanced Usage
📖 Usage Guide — Patterns, workflows, tips
🛠️ Tool Reference — Complete MCP API
🔧 Configuration — Environment variables
🐛 Troubleshooting — Common issues
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.
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
Found a bug? Have a feature idea? Open an issue or submit a PR!
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!
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