Use NotebookLM as a RAG System in Claude Code (MCP Tutorial 2026)

I turned Google NotebookLM into a RAG layer for Claude Code. Now I can query an entire documentation set from inside my terminal without copying files into the project. The setup takes under 10 minutes and uses one MCP server.

Why This Setup Exists

RAG (retrieval augmented generation) is what you reach for when you have a lot of reference material and you do not want to dump all of it into Claude's context window. Pinecone, Weaviate, ChromaDB, all great. They are also non-trivial to host.

NotebookLM already does the hard part: chunking, embedding, indexing, and answering queries over uploaded documents. It is free for personal use, the UI is fast, and the answers are grounded in citations from your sources.

The missing piece used to be programmatic access. With the new notebooklm-mcp server, you can query your notebooks straight from Claude Code.

What You Need

Claude Code installed
A Google account with NotebookLM access
One MCP server (we install it next)

Install the NotebookLM MCP Server

The community-maintained server is on npm. Install it as a Claude Code MCP server in one command:

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

That registers the MCP server for the current Claude Code project. Inside a Claude session, verify with:

/mcp

You should see notebooklm in the list of available servers and its tools.

Connect to Your NotebookLM Account

The first time the MCP server runs, it walks you through a browser-based Google sign-in. Approve, and it caches credentials so subsequent runs are silent.

The server reads which notebooks you have access to and exposes them as queryable resources. Each notebook becomes a tool Claude Code can call.

The Demo: Querying n8n Documentation

I wanted to ask questions about n8n's workflow engine from inside Claude Code without pulling n8n's docs into my repo. So I uploaded the n8n documentation export to a NotebookLM notebook called n8n-docs.

Inside Claude Code I asked:

Search my n8n-docs notebook for how to use the Webhook trigger node and summarize the options.

Claude calls the MCP tool, NotebookLM searches the indexed docs, returns the relevant passages with citations, and Claude synthesizes a short answer in the terminal. The citations include the section name and URL so I can verify in the source.

Total round-trip: a few seconds. No context-window cost for the full docs. No need to paste anything.

Where This Pays Off

The pattern matters more than the n8n example. Any time you have a body of knowledge that does not change often but is too big to dump into context, NotebookLM plus this MCP server is the lazy-developer's RAG:

Internal product docs (PDFs, Google Docs)
API references for tools you use occasionally
Research papers you want to reason about
Onboarding guides for a new codebase
Personal notes you have collected over years

Upload to NotebookLM once. Query from Claude Code forever.

The Trade-offs (Honest)

Latency: NotebookLM queries go over the internet. Expect 1 to 3 seconds per call.
Update lag: When source docs change, you need to re-upload the file to NotebookLM. There is no auto-sync.
Free tier limits: Google caps the size and number of notebooks. Fine for personal use, watch the limits at team scale.
Not for live data: RAG over docs is not the same as RAG over a live database. For that, build a domain-specific MCP server.

What the MCP Server Actually Does

Under the hood the server uses NotebookLM's web interface as a programmatic surface. Each query goes through a headless browser session (cached after the first sign-in). Each notebook you have is exposed as a separate tool so Claude Code can pick the right knowledge base for the question.

Source for the server: github.com/jamsocket/notebooklm-mcp

Subscribe to AyyazTech on YouTube for more MCP server tutorials and Claude Code workflow videos.