If you’ve ever wanted Claude to actually use your NotebookLM data — to generate podcasts, infographics, videos, or do deep research — then you’re going to love this.
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Most people never realize Claude can be connected directly to NotebookLM.
That’s where the MCP server setup comes in.
With just one GitHub project, you can bridge Claude and NotebookLM so they talk to each other — giving you a new way to automate research, generate content, and even build interactive media from your notes.
Why the MCP Server Setup Matters
Normally, NotebookLM sits in its own world.
You upload files, you get insights, but it’s isolated.
Claude, on the other hand, can analyze, summarize, and generate anything — but it doesn’t have access to your NotebookLM memory.
The MCP server setup fixes that.
It connects both worlds so Claude can reach into your notebooks, fetch data, create media, and even run commands like “create infographic,” “generate audio,” or “summarize across notebooks.”
That’s where things get fun.
Setting Up the MCP Server
You don’t need to be a coder.
It’s literally copy, paste, and run.
Here’s the basic flow:
You grab the GitHub repository called NotebookLM MCP Server, paste the link inside Claude Code, and run it.
Then Claude Code will install everything you need locally — no extra API costs, no cloud setup.
Once installed, you open your Claude settings, edit your config file (called desktop_config.json), and paste the MCP server details.
Hit save, restart Claude, and boom — you’ve connected your NotebookLM to Claude.
What Happens Next
This is where it gets wild.
Inside Claude’s chat window, you’ll see a new connector — “NotebookLM MCP.”
That means Claude can now talk to your notebooks directly.
You can give it natural language commands like:
- “Create an audio summary from this notebook.”
- “Generate an infographic about this research.”
- “Do deep research across all my 122 notebooks.”
Claude will go off, read your data, and generate whatever you asked for — directly from NotebookLM.
You can even view progress logs, open generated files, and control the whole process without leaving Claude Code.
Automating Your Entire Workflow
Think about this for a second.
Before MCP, you’d have to open NotebookLM, manually copy insights, and paste them into another tool to generate visuals or audio.
Now, with the MCP server setup, Claude becomes your automation bridge.
You can trigger audio summaries, infographics, and videos — all inside one chat.
And because Claude MCP can run locally, it works faster and more privately than cloud setups.
Example: Turning Notebooks into Podcasts
Let’s say you’ve got a notebook full of your marketing notes.
You can tell Claude:
“Use NotebookLM MCP to create an audio version of this.”
Claude will send the command to NotebookLM, process your notebook data, and generate a podcast-style audio summary automatically.
You could then ask it to create a matching infographic or even a short video script from the same notes — all without leaving Claude Code.
It’s basically like having your own AI content studio powered by your past research.
NotebookLM + Claude = The AI Dream Stack
Once you have this setup, you can also connect Claude to other MCP servers like AppleScript or Browser MCP — meaning you can control your local machine and your browser too.
That’s when you start building your own AI command center.
But for most creators, the biggest unlock is this:
NotebookLM MCP turns Claude into a creative partner that understands your data.
Instead of starting from scratch, it uses your notebooks to generate custom insights, scripts, or visuals that reflect your actual knowledge base.
Where It Gets Even More Powerful
Let’s talk about real automation.
You can chain MCP servers together.
For example:
- Use NotebookLM MCP to pull your notes.
- Use Anti-Gravity or OpenCode to code an app.
- Use Claude Code to automate design updates.
All within one connected workflow.
That’s why I say the MCP server setup is the missing piece of the modern AI builder’s stack.
If you’re serious about building with AI, this is where you start.
Real-World Use Case: Deep Research in Seconds
Imagine running a deep-research query like this:
“Search across all my AI agent notebooks and summarize the top trends in 2026.”
Claude MCP will instantly pull data from every connected NotebookLM document, organize insights, and return a cohesive report — all in one chat.
That’s not just automation.
That’s leverage.
You’re multiplying your output without adding more hours.
Why Most People Fail with MCP Setup
They overcomplicate it.
The setup itself takes 5 minutes.
But people try to customize before they even connect it.
Here’s the truth:
Run the GitHub as is.
Test the default commands.
Only then tweak your setup for specific use cases.
That’s how you avoid errors and get the connection stable from day one.
How I Use It in My Business
In my workflow, I use the MCP server setup daily to control my NotebookLM library.
When I record a video, I drop the transcript into NotebookLM, summarize it with Claude MCP, and instantly generate:
- An audio overview
- A thumbnail infographic
- A 1-minute short script
That’s three content assets from one notebook, created in minutes.
And since it all runs locally, it’s private, fast, and free.
Key Takeaways
- MCP server setup connects Claude to NotebookLM.
- It lets Claude access your data, generate visuals, and automate workflows.
- You can run it locally with Claude Code — no coding needed.
- The setup takes minutes but saves hours every week.
- You can scale your entire content process with it.
FAQs
How do I install the NotebookLM MCP server?
Grab the GitHub repo, run it inside Claude Code, and paste the config into your desktop JSON. Restart Claude and you’re done.
Can this work with other tools like Anti-Gravity or OpenCode?
Yes. You can use the same MCP integration logic to connect Claude to any tool that supports local APIs.
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.
What can Claude create using NotebookLM MCP?
Audio summaries, infographics, videos, deep-research reports, and even app specs based on your notebooks.
Is it free?
Yes — the MCP server is open-source, and you can run it locally without cost.
