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Show HN: Browserbeam – a browser API built for AI agents
I often use LLMs to automate different workflows, some of which include browsing the web and gathering data. At some point I started noticing a few things that bothered me: the browser interactions were clunky, as if the agent was struggling to "see" and understand the page, and as a result, many tokens were wasted. Same for knowing when the page is actually ready or not.<p>I started digging deeper and at some point I just bluntly asked in the Cursor chat the following question: "I ask you, as an LLM that uses these headless browsers, what do you wish people would build to make your work easier?"<p>And it worked because I expanded the "Thinking" section and I saw: "The user is asking me a really interesting meta-question ..." and after that it just listed top 10 most painful issues related to the agent<->browser interaction.<p>So I started building a browser API that returns what LLMs actually need, not what browsers return.<p>Fast forward a few weeks and here we are. A REST API built specifically to help LLMs interact with real browsers.<p>Instead of reading raw HTML, you get markdown, page map, short refs (e1, e2) for clicking instead of CSS selectors, a stable flag when the page is ready, diffs after each step, the list of all interactive elements (links, buttons, inputs), automatic blocker dismissal and a small extract step that returns structured JSON from a schema you describe.<p>Official SDKs for Python, TypeScript, Ruby. MCP server for Cursor and Claude Desktop.<p>Would appreciate any feedback, especially on the API design.
Browserbeam targets a high-growth niche in AI agent infrastructure by optimizing the 'agent-to-browser' interface, which is a significant friction point. While the product features are highly practical and developer-centric, the project currently lacks traction, team pedigree, and a clear defensive moat against well-funded competitors like Firecrawl or MultiOn.