What Is Hyperbrowser and What Does It Provide for AI Agents?

Updated

Hyperbrowser is a cloud platform that gives AI agents three things in one place: a browser to work in, isolated compute to run code on, and web data APIs to pull structured content from sites. It fits developers and teams building agents that need to log into real websites, execute code safely, or extract page data at scale. You connect through Playwright, Puppeteer, the Node.js or Python SDKs, the CLI, or MCP, and you can start with a free account that includes 5,000 credits.

The three core offerings

Cloud-hosted Chrome sessions

You control Chrome through an API rather than running it locally. Point Playwright or Puppeteer at a cloud session, and the platform handles the browser infrastructure. Sessions can keep logins between runs, and you can watch a session live while it works. The site reports startup from request to ready browser at under 500 ms, and cites 100M+ sessions run and 1,000+ concurrent isolated browsers.

This matters when your agent needs a real browser state—cookies, a logged-in profile, a page that renders with JavaScript—rather than a simple HTTP fetch.

Isolated sandboxes (microVMs)

Sandboxes are separate virtual machines where your agent can install dependencies, run commands, and expose local services without touching your application environment. You can save the environment as a snapshot and restore it in later runs, so a prepared setup doesn't have to be rebuilt each time.

A minimal SDK example from the site:

const vm = await client.sandboxes.create({
  imageName: "node",
});

await vm.exec("echo Sandbox ready");

await vm.createMemorySnapshot({
  snapshotName: "node-base",
});

The pattern is: create a sandbox from an image, run commands inside it, then snapshot the state for reuse.

Web API for fetching, crawling, and searching

The Web API fetches a page, crawls a site, or searches the web, and returns Markdown, HTML, screenshots, or JSON matching a schema you define. A fetch call can request multiple output formats at once:

await client.web.fetch({
  url: "https://example.com",
  outputs: {
    formats: ["markdown", "links"]
  }
});

This is the lighter path when you need page content rather than an interactive browser session.

Running agent tasks from a prompt

Beyond raw browser and compute access, Hyperbrowser can run browser tasks from a prompt using HyperAgent, Browser Use, or computer-use models inside a managed browser. You send a task, inspect the steps the agent took, and retrieve the result. The site's example is a flight search from Los Angeles to San Francisco on Google Flights—a task that requires navigating a real site rather than calling a clean API.

What supports production use

The platform lists several operational features that matter once you move past a prototype:

  • Saved state — reuse browser profiles with cookies and logins; restore sandboxes from memory snapshots.
  • Session recordings — watch sessions live and replay recordings to debug a failed run.
  • Isolated execution — commands run in VMs separate from your application.
  • SDKs and integrations — Playwright, Puppeteer, Node.js and Python SDKs, CLI, and MCP.
  • Security and access controls — the site references encryption, access controls, and independent security assessments, with a separate security overview page.

Who it is for, and when it fits

Choose Hyperbrowser when your agent's job depends on interacting with websites as a user would—maintaining a login, clicking through a flow, or rendering dynamic pages—or when it needs to run untrusted or dependency-heavy code in isolation. The combination of browser sessions, snapshots, and replayable recordings is aimed at teams that need to debug and reproduce agent runs, not just fire one-off requests.

If you only need to pull static page content, the Web API's fetch-and-return-Markdown path is the simpler entry point. If you need full browser control, start with a Playwright or Puppeteer connection to a cloud session.

Getting started

The site offers a free account with 5,000 credits included, plus a copyable agent setup prompt and a demo booking option. A practical first step is to run one fetch through the Web API to confirm your SDK connection, then move to a browser session or sandbox depending on whether your task needs interaction or code execution. Pricing beyond the free tier is listed on the pricing page; check it there before committing to volume, since the free credits are a starting allowance rather than a usage guarantee.