Introduction

In recent years, the evolution of AI technologies has made it easier to learn through audio, not just text. This article introduces a method to study the latest concepts such as Model Context Protocol (MCP) using Google's NotebookLM by turning technical documents into a podcast-style audio.

What is NotebookLM?

NotebookLM is an AI-powered research and note-taking tool developed by Google Labs. Based on Google Gemini, it can summarize documents, generate Q&A pairs, and even produce spoken summaries through its Audio Overview feature introduced in 2024. This allows users to learn complex topics effortlessly via audio.

What is MCP (Model Context Protocol)?

MCP is a protocol designed to enhance context sharing between large language models (LLMs), enabling better cooperation among distributed AI agents. It has been gaining attention from major AI communities including Anthropic, GitHub, and a16z for its role in building next-generation AI systems.

How to Create a Podcast with NotebookLM

1. Collect Information

Start by gathering high-quality articles from Google search and tools like ChatGPT. Here are some recommended resources:

2. Import into NotebookLM

Log in to NotebookLM and create a new notebook. Paste the URLs or upload documents you've collected. NotebookLM will automatically summarize and organize the content into a knowledge base.

This is the menu of NotebookLM. This example is Japanese but you can change Web UI language and output language into your favorite language like English.

If you create a notebook, you can input source informations like URL, documents and texts

3. Generate an Audio Overview

Click on the “Audio Overview” button in the top-right corner of the NotebookLM interface to automatically generate a podcast-style audio summary. The generated audio is structured in a conversational format, making it easy to follow. I customized a request for the podcast.

These podcasts typically run for 10–15 minutes and are perfect for efficient learning during spare moments.

NotebookLM × RAG Approach

This method resembles Retrieval-Augmented Generation (RAG). You collect external knowledge sources, and NotebookLM processes that content to generate summaries and podcasts. This allows you to consume the latest technical information via audio on demand.

Use Cases and Future Potential

The approach introduced here can be applied beyond MCP:

Catching up on tech trends
Creating internal training content
Audio explanation of academic papers
Pre-reading business materials

In the future, NotebookLM may offer audio export or enterprise integration, opening new possibilities for professional use.

Precautions and Security

Be mindful of the following when using NotebookLM:

Terms differ for personal and enterprise accounts
Avoid uploading confidential or copyrighted data
Not suitable for medical, legal, or financial advice

Google explicitly states that personal data from NotebookLM is not used to train AI models. Understanding the terms and using it appropriately is crucial.

Conclusion

NotebookLM opens up a new way of learning: through your ears. By transforming technical articles into audio summaries, even advanced topics like MCP can be studied with minimal effort.

If you're looking for an efficient way to stay current in the AI field, try using NotebookLM to generate your own personalized podcasts.