Scalebrowser is a browser built for AI agents that need to operate real websites at scale. Instead of treating each automation run as a fresh, anonymous session, it gives every agent a persistent, isolated profile with its own logins, cookies, device fingerprint, and inbox. The result is a browser that behaves like a returning visitor rather than a new device, which matters for any task that depends on staying signed in across sessions.
What it offers
The product centers on three layers: the browser, the signing-in process, and the agent interface.
- Persistent, isolated profiles. Each profile keeps its own identity, cookies, and device values across restarts. Profiles do not share state, so multiple accounts can run side by side without interfering with each other.
- Automated sign-in handling. Stored passwords are typed into forms without being exposed to the agent, two-factor codes are computed inside the profile, and passkeys survive crashes and window closures. Permission prompts and device pickers are answered automatically instead of halting a run.
- Agent-friendly page access. The agent reads a page once and then only receives what changed, which keeps token usage low over long runs. Captchas, run trails, and secret handling are built into the same layer.
Who it is for
Scalebrowser suits teams and individuals running browser automation across many accounts or platforms. Typical scenarios include managing social media, marketplace, messaging, and business accounts; running nightly automation that must stay logged in; and connecting existing agent frameworks to a browser that already has the right session. It works with MCP clients such as Claude, Cursor, and ChatGPT, as well as Python and Node SDKs over direct CDP, so existing agent logic can stay in place while the browser underneath is swapped out.
What makes it different
The main distinction is the combination of persistent identity and agent-oriented efficiency. Many browser automation tools start each run from a clean slate, which forces repeated logins and triggers detection. Scalebrowser keeps the same visitor identity across runs, handles the login and verification steps that usually break automation, and reduces the amount of page content sent to the model. It also reports captcha handling on live widgets and detector-site passes from its own audit bench, giving a concrete picture of how it performs in practice.
For anyone running agents that need to stay signed in and operate across multiple accounts, Scalebrowser provides a browser layer designed around that requirement rather than adapted to it.
