AI agents that browse the web need a fleet of isolated browsers, here is a brokerless scheduler for it

Give an AI agent one browser and it is easy. Give a hundred agents their own browsers and you have an infrastructure problem.

Browser automation at scale has an awkward shape. Each browser wants real resources, a real filesystem, and real isolation, because you are running untrusted pages, scraping targets that fight back, or agent sessions you do not want sharing cookies. So you cannot just spin up a thousand threads. You end up managing containers, then managing the machines the containers run on, and then you are writing a scheduler.

Machineuse is that scheduler, built for exactly this workload. It is a Python platform that creates, schedules, and manages isolated browser instances across multiple worker nodes, with load balancing and a snapshot-based dormancy trick to reclaim resources from idle instances. This post covers how it places work, how dormancy works, and where the design constrains you.

The project tags itself for chromium, browser-automation, and mcp, so the agent-browser fleet is squarely the workload it has in mind. One thing to be precise about, though: machineuse schedules and isolates the containers. What runs inside, the browser and your automation or agent code, is yours. It is fleet infrastructure, not an agent framework. That separation is the point. You bring the agent, it brings the machines.