NativeMindExtension: An On-Device Browser Assistant Built Around Ollama
NativeMind: Your fully private, open-source, on-device AI assistant
At a glance
- What is it?
- NativeMindExtension is a TypeScript browser extension that routes chat, page summarisation, translation and PDF or image questions through a locally running Ollama server, with WebLLM listed as a trial alternative. The design keeps prompts on the machine, but it also makes Ollama a hard dependency for the full feature set.
- Who is it for?
- Adopt NativeMindExtension if you already run Ollama and want page summarisation, translation and PDF or image questions to stay on your own hardware. Skip it if you cannot install a local model server, since the README treats Ollama as the recommended path and WebLLM only as trial support.
- Can I use it commercially?
- Yes, with strict conditions. AGPL-3.0 is a network copyleft licence: if people use a modified version over a network, for example as a hosted service, you must offer them its source code under the same licence.
- Is it still maintained?
- Yes. The repository last received commits 177 days ago.
- What is it written in?
- Mainly TypeScript, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 15, 2026, and from our analysis. They are not legal advice.
DEEP OPEN-SOURCE ANALYSIS
The problem NativeMindExtension targets: cloud assistants that see your pages
Every mainstream browser assistant works by shipping the page text, your prompt, or both to a remote endpoint. That is fine for public documentation and awkward for anything behind a login. NativeMindExtension takes the opposite position. The README describes it as a fully local browser extension built on Ollama, and the badge row lists Data: On Device and Tracking: None. The audience is therefore narrow and identifiable: people who already have a machine capable of running a model, who are willing to install and maintain Ollama, and who would rather lose some answer quality than send page contents off the device. It is not aimed at someone who wants a hosted assistant with no local setup. The README's own framing, a private open-source alternative to ChatGPT, sets that expectation directly, and the installation section assumes you will follow a separate Ollama setup guide before the extension is useful.
How the extension is put together: a browser client over a local model server
The architecture visible in the material is a split between the extension and a model runtime. The extension is written in TypeScript and ships for Chrome and Firefox, with Brave and Edge listed as supported in the installation section and an Edge badge marked Coming Soon. Ollama runs as a self-hosted local server, which the README describes as giving maximum control, and the extension talks to it rather than to a vendor API. WebLLM appears as a second path, described as Trial Support, which matters because WebLLM executes models inside the browser through WebAssembly instead of through a separate server process. That gives two distinct data flows: one where the model process lives outside the browser, and one where the model runs in the page context. The feature list sits on top of these: contextual awareness across tabs, page summarisation, bilingual translation with a side-by-side view, chat with PDFs, chat with images, and writing tools for rewriting and proofreading. An agent layer is described as breaking complex requests into multi-step actions with tool use. The README does not document the message format, storage schema or permission model, so the internal plumbing is not something you can evaluate from the repository description alone.
Getting it running: store install, Ollama, then a model
There are two installation routes and the README only fully specifies one. The store route is a click from the Chrome Web Store or the Firefox add-ons listing, followed by pinning the extension to the toolbar. The README's quick start then gives three steps: pin the extension, follow the Ollama setup guide, and click the NativeMind icon. The setup guide lives at nativemind.app/blog/tutorial/ollama-setup rather than in the repository, which means the exact commands are not in the material available here, and you should read that page before assuming a particular port or flag. What the README does state is the model side: Ollama is the recommended option, with Deepseek, Qwen, Llama, Gemma, Mistral and Phi named as supported families, plus gpt-oss compatibility. Model switching is a described feature, so the expectation is that you pull more than one model and change between them depending on speed or quality. WebLLM is the alternative runtime, and the README labels it trial support rather than a first-class path. If you want the offline-first behaviour the README describes, a model has to be downloaded first; the claim is that features work without an internet connection after that point.
The Ollama dependency is the real constraint, not the licence
The extension is a client. Without a reachable Ollama server, the README's recommended configuration does not exist, and the fallback is a runtime the project itself describes as trial support. That has practical consequences. A laptop without the disk space or memory for a capable model will produce slow or poor answers, and there is no cloud option to fall back on by design. The browser support matrix is also uneven: Chrome and Firefox have store listings, Brave is grouped with them in the installation text, and Edge is marked as coming soon, so an Edge user reading the badge row should not expect a store install today. Two more gaps are worth naming. The README does not publish minimum hardware requirements or model size guidance, so capacity planning is guesswork until you read the setup guide. And the agent feature, described as autonomous task execution with tool integration, is the kind of capability where the failure modes matter most; the README gives no detail on what tools are exposed, what permissions they need, or how a multi-step run is stopped. Treat that part of the feature list as unverified until you read the code.
Where a local-first extension loses to a hosted assistant
The obvious alternative is a hosted assistant such as ChatGPT in a browser tab, and the difference is not cosmetic. A hosted assistant runs a frontier model on hardware you do not own, so it answers faster and better on a thin client, and it needs no local server, no model downloads and no disk budget. It also sees your page content if you paste it in. NativeMindExtension inverts both properties: weaker models on your own hardware, in exchange for prompts and page text that stay on the machine. There is a second comparison closer to home. Running Ollama directly and using its own interface avoids the extension entirely and removes a moving part, but you lose the browser integration that is the whole point here: summarising the page you are on, translating a selection in place, and carrying context across tabs. If your work is mostly pasting text into a chat window, the extension adds little over the Ollama CLI or a local chat UI. If your work happens inside web pages, the integration is the value.
Release cadence, AGPL-3.0 and what maintenance actually costs you
The release history shows a steady rhythm: 1.12.3 in early March 2026, then 1.12.4-beta.0 and 1.12.4 later the same month, with the latest push matching the 1.12.4 tag. That pattern suggests active development with a beta channel ahead of stable releases, which is useful if you want to test changes early, and a mild risk if you pin to stable and the model-facing behaviour shifts between versions. Upgrade cost is mostly on the Ollama side: model families named in the README change over time, and a model you standardised on can be superseded. The licence is AGPL-3.0. For an individual installing from the Chrome Web Store or Firefox add-ons, that is unremarkable. For a company that wants to fork the extension, modify it, and offer it to users over a network, the AGPL's network clause is the part to read carefully, since it can require source disclosure for modified versions served to remote users. This is not legal advice; if you plan to redistribute a modified build internally, have counsel read the licence text rather than a summary.
Who should install NativeMindExtension, and what to check first
Install it if you already run Ollama, your browser is Chrome, Firefox or Brave, and your main use case is interrogating pages, PDFs and images without shipping them anywhere. The extension is a thin client over a server you control, and that is the correct shape for the privacy claim it makes. Do not install it expecting a hosted assistant's answer quality, and do not install it on a machine where you cannot run a local model at all, because the recommended path simply will not exist. Before you commit, do three things: read the Ollama setup guide at nativemind.app/blog/tutorial/ollama-setup rather than guessing at connection details, decide which model family from the README's list you can actually run at acceptable speed on your hardware, and if you are evaluating the agent features, read the source, because the README describes autonomous multi-step execution without documenting the tools or their permissions. The project is maintained and shipping; the open question is whether your machine can carry the model it depends on.
Editorial conclusion
Adopt NativeMindExtension if you already run Ollama and want page summarisation, translation and PDF or image questions to stay on your own hardware. Skip it if you cannot install a local model server, since the README treats Ollama as the recommended path and WebLLM only as trial support. Before committing, check the Ollama setup guide linked from the README, confirm your browser build is one of Chrome, Firefox, Brave or Edge, and read the AGPL-3.0 terms if you intend to redistribute a modified build.
Community notes