BrowserOS neo

BrowserOS neo is a local, open-source Chromium browser that gives AI agents control of websites through your existing signed-in accounts. It suits technically confident users who want automation on their own computers and can provide separate AI-provider credentials. Its strongest case is private, replayable browser work; its biggest compromises are shared login sessions and the responsibility for those provider keys.

Overview

BrowserOS neo lets an agent open tabs, follow links, press controls, and read live pages as though it were operating your browser. Because it works inside sessions you already use, it can address practical tasks such as inbox administration, trip planning, comparing prices, searching for jobs, drafting marketing posts, and following up with sales leads. The same capability means you should only connect accounts where delegated actions are acceptable.

The software runs locally. Sessions, screenshots, replay videos, settings, and logins remain on your machine rather than being transmitted to a server operated by the maker. A one-click Chrome login import can reduce migration work for an existing Chrome user. Local storage is a substantial privacy advantage, but it also leaves setup, machine security, and account permissions in your hands.

Key features

MCP connections

BrowserOS neo connects to agents through MCP, including Claude Code, Claude Cowork, Cursor, Codex, VS Code, Zed, and GitHub Copilot. That broad set makes it useful when your preferred assistant already lives in one of those tools. You bring your own AI provider keys, so there is no bundled model allowance; the ongoing provider cost and key management are yours.

Concurrent work and replay

Several agents can work simultaneously in separate tabs while you continue browsing. This can shorten multi-step workloads, although all agents draw on the browser sessions already signed in. Every run is saved as a scrubbable video, giving you a practical way to review what happened or revisit a useful sequence rather than relying on a text log.

Token-conscious automation

The agent receives compact page snapshots instead of raw HTML and can batch actions in one call. That design is intended to reduce token use and can make repetitive navigation more economical with your chosen provider, though actual savings depend on that provider and the task.

Open-source, shared profiles

BrowserOS neo is released under AGPL-3.0, which is relevant to developers who want inspectable software or plan modifications. Agent profile isolation is on the roadmap rather than a current feature. Until then, agents share the browser's signed-in sessions, an important boundary for households, teams, or accounts with different permission levels.

Pricing

BrowserOS neo — free. The plan is free and open source under AGPL-3.0, runs locally, and requires you to bring your own AI provider keys. There is no free trial because the product is already free, and no separate paid tier or included provider quota is stated. It is a good fit for individuals who already pay for or otherwise have access to a compatible AI provider. It is less suitable if you want one subscription covering both browser automation and model usage.

Platforms

BrowserOS neo uses the Chromium engine and is offered for Linux, macOS, and Windows. The browser-agent entry specifically identifies macOS and Windows as supported platforms. Local execution is consistent across the product's privacy model, but the published platform information does not promise identical behavior across operating systems.

Who it's for

Choose it if you want agents to act in real, authenticated websites while keeping browser data on your own computer. Developers and automation-oriented users will benefit most from MCP support, open source, concurrent tabs, and replayable runs. It is a poor match for anyone seeking isolated profiles per agent, a hosted service that handles model access, or a turnkey experience without managing provider keys and account risk.

Pros and cons

Pros

• Local privacy: logins, settings, screenshots, sessions, and replays stay on your machine.
• Useful agent coverage: MCP links several major coding and assistant environments.
• Auditable runs: scrubbable video replays make agent activity easier to inspect.
• Parallel operation: separate tabs allow multiple agents to work while you browse.
• No software charge: the free AGPL-3.0 release lowers the barrier for personal use and experimentation.

Cons

• Shared logins: agents use existing browser sessions, while per-agent isolation remains a roadmap item.
• Bring your own keys: model access and its costs are separate from the browser.
• High account responsibility: an agent can act inside authenticated services, so mistakes affect real accounts.
• Platform ambiguity: the general listing includes Linux, but the browser-agent entry names only macOS and Windows.

Alternatives

BrowserOS is the closest alternative if you want a free, open-source browser with built-in AI agents across extension, Linux, macOS, and Windows. Norton Neo is a better choice for broad device coverage and included unlimited AI, with VPN allowances tied to its default-browser status. Pick Comet for a free, closed-source browser on Android, iOS, macOS, or Windows. Arc Search fits readers wanting a free mobile browser rather than local MCP automation. Aside suits users who prefer freemium routines with monthly credits and a bring-your-own subscription model. Genspark AI Browser offers a no-subscription, no-limit on-device tier, while its team plan costs $30 a month. MoltBrowser is another free-forever, fully open-source option. Polar is worth considering if starting credits, daily credits, and paid individual features matter more than an entirely local browser.

Verdict

BrowserOS neo is a strong recommendation for developers and privacy-conscious individuals who want MCP-connected agents to perform real browser tasks locally and leave a replay behind. Choose it for local control, open source, and transparent runs. Look elsewhere if shared authenticated sessions are unacceptable or if you want model access, quotas, and profile isolation included in a managed plan.