fastbrowse positions itself as browser automation with results you can verify. Rather than returning opaque agent output, it completes a workflow and hands back an answer supported by quoted page text, so teams can check what the browser actually saw. It runs locally or in a hosted cloud browser and is MIT licensed, which makes it easy to inspect and adapt.
The core mechanism is an indexed list of the controls a page offers. The agent, called Jev, selects an operation and target from that list instead of inventing selectors. Credentials are handled separately: a secret is passed by name and resolves only on the allowed origin, so passwords never enter model prompts. Code also governs spending and authorization.
It fits developers building agent workflows, QA and test automation engineers, and data teams that need schema-validated output from web tasks. The interactive replay example, signing in and completing a checkout on a demo store, shows the intended scope: multi-step tasks with a readable trace of steps, timing, and model cost.
Start with the quickstart and docs, then try a small workflow such as a login-and-checkout flow to see how citations and secret handling behave. Use the benchmarks and security pages to judge fit before scaling. In short, fastbrowse trades general-purpose browsing for constrained, auditable automation.
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