Quick answer: five maintained ways to get NotebookLM’s workflow without uploading your files to Google. Open Notebook is the closest feature clone, self-hosted. SurfSense is the self-hosted pick if your agents need it too. AnythingLLM is the all-in-one desktop RAG app. Hyperlink is closed-source but truly offline and indexes folders in place. StashBase — ours — keeps your folders as the library and lets any agent search them over MCP. Almost as many alternatives have died since 2023 as survive.
Checked September 6, 2026: stars, releases, commit logs, and each project’s docs for how files actually get in. Google renamed NotebookLM to Gemini Notebook in July 2026 — same product; this post uses the name people still search.
What you’re replacing
NotebookLM passed 30 million users this year, so credit first: grounded answers with citations, Audio Overviews, zero install. If you want a generated podcast or a shareable notebook, nothing below replaces that.
The costs are structural. Every notebook is a pile of uploaded copies — the paper you annotated on disk is not the paper the notebook read, and the same PDF gets uploaded into three projects. And the consumer version has no API: the most popular workaround for reaching it from your own agents is a 3.4k-star MCP server that drives the web app through a headless browser.
So “alternative” is really three questions. Where do files live — uploaded again, or in place? What persists — chat scrollback, or artifacts you keep? Who can query it — that app’s chat box, or the agents you already use?
Open Notebook — the feature clone
38.2k stars, very active. Docker self-host, sources go into its own database, and it matches NotebookLM feature for feature: cited chat, notes, podcast generation with up to four configurable speakers. 18+ model providers including Ollama, so it runs fully offline. REST API and an official MCP integration.
Pick it if you want NotebookLM itself, minus Google. Accept that your files still get imported into a second store, one notebook at a time.
SurfSense — the one built for agents
16.1k stars, active, and repositioned this year as “the open-source NotebookLM alternative for AI agents.” Self-hosted; ingests 50+ formats, syncs cloud drives, and can watch a local folder. Every connector — including web, Reddit, and search scraping — is exposed as a REST endpoint and an MCP tool.
Pick it if the consumer is an agent pipeline and you want live web data next to your documents. Its center of gravity is web research, not your local library, and ingested files live in its store, not your folders.
AnythingLLM — the all-in-one desktop app
65.7k stars, 1M+ Docker pulls, very active. Desktop or Docker, workspaces of uploaded documents, local vector store, agents, and it speaks MCP — as a client, pulling tools in. Your documents go into its workspace; live re-sync of changed files is still a beta feature, and external agents can’t query it as a knowledge source.
Pick it if you want one private app that chats with your documents and runs local models, and your other AI tools don’t need what’s inside it. AnythingLLM vs NotebookLM compares the two directly.
Hyperlink — offline, in place, closed
The newest entrant, from Nexa AI, promoted by NVIDIA after ChatRTX was retired. Free, closed-source, fully on-device: point it at folders and it indexes thousands of files where they sit — no upload step at all — then answers with line-level citations from a local model.
Pick it if “never touches the network” is the whole requirement. It ends at its own chat box: no API, no MCP, no artifacts — the answers aren’t reusable anywhere else.
StashBase — your folders, your agents
Ours, so judge accordingly. StashBase opens the folders you already have and derives what search needs in the background — extracted text for PDFs and DOCX, and OCR for images. Recordings play but aren’t transcribed. Nothing moves; the index rebuilds from the files. Search is keyword (offline, no account) plus semantic, and the same library is served over MCP, so Claude Code, Codex, Claude Desktop, or Cursor query it instead of each keeping its own copy. Build Wiki Pages goes one step further than chat: the agent writes visible Markdown overview pages into a wiki/ folder you own.
Pick it if the point is a living library your own agents search. It’s an app you run, and there’s no podcast button — the FAQ is honest about the rest.
The graveyard
This category kills products, which is worth knowing before you commit your library to one:
- GPT4All — 77k stars, the original “point it at a folder” app. Zero commits in 2026; “Is GPT4all dead?” is an open issue.
- Reor — the local AI notes app. Archived May 2025.
- NVIDIA ChatRTX — deprecated January 2026.
- PrivateGPT — 57k stars from the 2023 wave; relaunched mid-2026 as a developer backend. Respectable, but no longer something you chat with.
Khoj (37k stars, folder sync, self-hosted) isn’t in the graveyard, but a dozen commits since June is not a heartbeat either.
The pattern in who died: “local chat with your docs” as the entire product keeps not surviving. The survivors clone NotebookLM outright, serve enterprises, or stopped trying to be the AI and started serving the AI you already have.
Not actually alternatives
Jan and LM Studio are local chat clients — you attach a file to a conversation, there’s no library. Msty does folder RAG but seals it into a proprietary “Stack,” closed-source. Obsidian is an editor over local Markdown, and the right base if you’d rather build the wiki layer yourself with Claude Code. Notion is the same trade as NotebookLM with better tables.
Side by side
| Files get in by | What persists | Your agents | Offline | Pulse | |
|---|---|---|---|---|---|
| Open Notebook | import into its DB | notes, podcasts | API + MCP | ✓ with Ollama | very active |
| SurfSense | import, drive sync, folder watch | reports, podcasts | API + MCP | ✓ self-hosted | active |
| AnythingLLM | upload to workspace | chat | ✗ (MCP client only) | ✓ | very active |
| Hyperlink | indexes in place | chat | ✗ | ✓ fully | active, closed |
| StashBase | indexes in place | wiki pages you own | ✓ MCP server | keyword search ✓ | active |
| NotebookLM | upload to notebook | notes, podcasts | ✗ consumer / enterprise API | ✗ | 30M users |
The underlying difference is still one design decision: NotebookLM asks you to bring your files to the AI’s library. The local alternatives either rebuild that library on your machine — or bring the index to your files and let any AI you already use read it. If you’re building your own, three decisions come before any tool.