NotebookLM MCP Setup: Automate Everything Inside Claude Code

What if you could control NotebookLM without ever opening the app?

What if you could research, create, and generate everything using one single chat inside Claude?

That’s exactly what the NotebookLM MCP setup does.

It connects NotebookLM with Claude Code and lets you automate your entire workflow in minutes.

No coding, no API headaches, no switching tabs.

Watch the video below:

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What Is NotebookLM MCP Setup?

The NotebookLM MCP setup is like a translator between your NotebookLM notebooks and Claude.

It uses something called the Model Context Protocol (MCP) — a fancy way of saying it allows two AI tools to “talk” to each other directly.

Here’s why that matters.

NotebookLM is incredible for storing information, summarizing data, and building knowledge bases.

But it’s limited.

Claude, on the other hand, is powerful at reasoning, coding, and generating.

When you connect NotebookLM with Claude Code, you get the best of both worlds — Claude’s creativity with NotebookLM’s accuracy.

You can literally chat your way into automating reports, podcasts, infographics, or entire client deliverables.

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Step 1: Install the NotebookLM MCP Server

Let’s start with setup.

Go to GitHub and search for NotebookLM MCP Server by Jacob.

This open-source connector is what bridges NotebookLM and Claude Code.

Download or clone the repository.

Open Claude Code and launch the terminal.

Paste in the GitHub command to install the MCP server.

Accept the terms, and it will begin syncing automatically.

Once it’s installed, you’ll see new commands appear in the terminal — things like:

• list_notebooks
• create_notebook
• generate_audio
• generate_infographic
• query_sources

You can even connect this same MCP setup with Gemini CLI, Cursor, or VS Code if you want a broader setup across your dev tools.

The point? You now have direct control over NotebookLM — right from Claude.

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Step 2: Configure MCP Inside Claude Code

Now we connect everything.

Open Claude’s Developer Settings and look for your config file:
CL Desktop Config.json

Paste the configuration code for your NotebookLM MCP setup.

Save, close Claude, then reopen it.

Once you relaunch, go to your connectors list — you’ll see NotebookLM MCP active.

If you see an error at first, don’t panic.

Claude may still be installing dependencies.

Give it a minute or two.

Then restart Claude again.

Now, your system is officially connected.

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Step 3: Control NotebookLM From Claude

Here’s where the fun starts.

You can now talk to NotebookLM through Claude, like this:

“Create an audio overview from NotebookLM.”

Claude automatically pulls your notebook data and generates a clean, narrated summary.

Or try this:

“Generate an infographic using NotebookLM MCP.”

Claude will visualize your notebook data and generate a beautiful chart or diagram.

You can even say:

“Create a video overview from my AI research notebook.”

Claude will build a full multimedia presentation, grounded in your own research.

This isn’t limited to summaries — you can query data, merge sources, or perform deep research inside multiple notebooks at once.

All hands-free.

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Step 4: Why The NotebookLM MCP Setup Changes Everything

Before, your workflow looked like this:

NotebookLM for research.

Claude for writing.

And you constantly switched tabs.

But now, they’re one.

You can research, create, summarize, and produce inside a single AI chat.

This means:

• Less context switching
• Faster project delivery
• No manual exporting or reformatting

It’s ideal for creators, coaches, agencies, and AI builders who want to automate the “grunt work” and focus on growth.

And since everything runs locally, your data stays private and secure.

If you want the templates and AI workflows, check out Julian Goldie’s FREE AI Success Lab Community here:
https://aisuccesslabjuliangoldie.com/

Inside, you’ll see exactly how creators are using NotebookLM with Claude Code to automate education, content creation, and client training.

You’ll also get access to prebuilt templates, setup guides, and automation workflows from top AI professionals.

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Step 5: What You Can Build With NotebookLM MCP

Here’s the crazy part — this isn’t just for research.

You can use the NotebookLM MCP setup to build real tools.

For example:

• Podcast automation: Upload transcripts to NotebookLM, then ask Claude to generate an AI-narrated episode.
• Infographic creation: Pull key stats from multiple notebooks and visualize them instantly.
• Client onboarding bots: Upload your service SOPs and have Claude answer client questions using your own documentation.
• Course material: Use NotebookLM’s organized data to create quizzes, summaries, and flashcards inside Claude.

Once this setup is active, your Claude environment becomes a full AI command center.

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Real Use Case: From Research to Business Tool

Let’s say you run an online education business.

You have dozens of training materials, scripts, and PDFs.

Normally, it takes hours to update lessons or repurpose that content.

With the NotebookLM MCP setup, you can upload everything to NotebookLM, then ask Claude to:

“Summarize these lessons into 5 training slides.”

Claude reads your NotebookLM sources, generates content, and even designs visuals in seconds.

This is exactly how I build courses and automation systems inside the AI Profit Boardroom community.

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Pro Tips For Better Results

1. Use small, high-quality notebooks.
   NotebookLM works best when you keep each notebook focused on a single topic.
2. Give Claude roles.
   Tell it, “Act as a UX designer” or “Act as a video editor.”
   This improves the accuracy and tone of your outputs.
3. Iterate, don’t automate once.
   Run multiple tests.
   Ask Claude to adjust formatting, colors, and tone.
   You’ll get professional-grade results in minutes.
4. Combine tools.
   Pair NotebookLM for data, Claude Code for automation, and Google Sheets for analysis.
   That’s a winning stack.

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FAQ

What exactly is the NotebookLM MCP setup?
It’s a bridge that lets Claude Code directly control NotebookLM using the Model Context Protocol.

Do I need coding experience?
Not at all. You just copy, paste, and run.

Is it free?
Yes, the GitHub MCP server is open source and free to use.

Can I run this offline?
Yes, the connection runs locally on your device for maximum privacy.

Where can I get templates to automate this?
You can access full templates and workflows inside the AI Profit Boardroom, plus free guides inside the AI Success Lab.