Alternatives
Products that do what Rasterport does
Give AI agents eyes on the web
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I use AI agents to build UI features daily. The thing that kept annoying me: the agent writes code but never sees what it actually looks like in the browser. It can’t tell if the layout is broken or if the console is throwing errors. So I built a CLI that lets the agent open a browser, interact with the page, record what happens, and collect any errors. Then it bundles everything — video, screenshots, logs — into a self-contained HTML file I can review in seconds. proofshot start --run "npm run dev" --port 3000 # agent navigates, clicks, takes screenshots proofshot stop It works with…
Mar 2026 · github.com
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Scan your website to see how ready it is for AI agents.
Apr 2026 · isitagentready.com
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Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make…
Jul 2026 · microsoft.github.io
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I've been building computer-use tools for a while, and I quietly launched this about a month ago (122 Stars on GH). I figured it was worth sharing here. Over the last few months, a lot of computer-use agents have come out: Codex, Claude Code, CUA, and others. Most of them seem to work roughly like this: 1. Take a screenshot 2. Have the model predict pixel coordinates 3. Click x,y 4. Take another screenshot 5. Repeat That works, but it's slow, expensive in tokens, and fragile. If the UI shifts a few pixels, things break. And the model still doesn't know what any element actually is. But the…
May 2026 · github.com
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Hi HN, My team and I are building Tabstack to handle the "web layer" for AI agents. Launch Post: https://tabstack.ai/blog/intro-browsing-infrastructure-ai-ag... Maintaining a complex infrastructure stack for web browsing is one of the biggest bottlenecks in building reliable agents. You start with a simple fetch, but quickly end up managing a complex stack of proxies, handling client-side hydration, and debugging brittle selectors. and writing custom parsing logic for every site. Tabstack is an API that abstracts that infrastructure. You send a URL and an intent; we…
Jan 2026
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Get 10x speed for building automations. AI copilot is here
2025
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2024 · webcrumbs.org
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Hey HN! We’ve been building an MCP server to help AI-assisted web app developers by using browser agents to test whether changes made by an AI inside an editor actually work. We've been testing it on scenarios like verifying new flows in a UI, or checking that sending a chat request triggers a response. The idea is to let your coding agent both code and evaluate if what it did was correct. Here’s a short demo with Cursor: https://www.youtube.com/watch?v=_AoQK-bwR0w When building apps, we found the hardest part of AI-assisted coding isn’t the coding—it’s tedious point-and-click…
2025 · github.com
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We recently built 2draw, a Drawful-style game where players draw on a shared canvas and race to guess each other's drawings, on tldraw, an infinite-canvas SDK for React. We started wondering what it would take to put an agent in that loop, as an opponent or a rival guesser, and dug into how an agent could read and draw on a tldraw canvas. That research turned into: Agent draw, a tool that lets an agent draw to the canvas for you while you present. You can try it right now, or grab the source: - Live demo: https://tldraw-agent-draw-demo.james-664.workers.dev - Source:…
Jul 2026 · techstackups.com
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