WebPilot – "Cursor" for the Browser

Hacker News

Hey HN I just launched the first version of WebPilot – a browser extension that turns your browser into something closer to an AI-powered assistant. Think of it like Cursor IDE, but for the web. You can give it commands like “click the login button,” “fill this form,” “scroll down and read comments,” or even “grab all the email addresses from this page” – and it’ll do it. It highlights elements, navigates between pages, works on sites like Reddit and HN, and can even take screenshots or copy stuff to your clipboard. I was inspired by the way Cursor integrates AI into coding(use it everyday for all my projects), and wanted to bring that same feel to the browser. Most of us spend hours online doing repetitive stuff, so why not let an AI handle it? What it can do so far: - Click buttons, fill forms, scroll pages – all by command - Extract data and interact with content on Reddit, Hacker News, etc. - Works with voice input (or just type commands) - Has utility tools like page clicks, inputs, screenshots, clipboard copy - Super customizable – hotkeys, model selection(now OpenAI and Anthropic, others is progress), profiles for specific sites with automatic choosing based on opened website - MCP support via SSE transport (for STDIO you could use mcp-proxy of supergateway) Why I’m posting here This is very much a “v1” – it works, but I’m still shaping what it should be with feedback from early users. I’m looking for people who want to try it out and help shape the future of browser automation with AI. There’s a one-time early adopter deal ($199) that gives you all premium features forever + GitHub read access. No subscriptions, no recurring charges. Would love any feedback or feature ideas from the HN crowd – especially what you’d want to use a browser agent like this for. Thanks!

Visit product View on Hacker NewsMar 28, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, cursor, model · Missing: mac, agents, macos

97%97% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released

34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: recurring, subscription · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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