Sc

ScrapeCopilot – Notebook Code Interface + Puppeteer + AI Copilot

Hacker News

ScrapeCopilot – Notebook Code Interface + Puppeteer + AI Copilot

Hi HN, I’m Eric, and I’m building ScrapeCopilot, an AI assistant designed to eliminate friction in browser automation development. Here is the link to VS Code extension - https://marketplace.visualstudio.com/items?itemName=scrapeco... I've built browser automations for more than 5 years, and the constant frustration was always the sheer friction involved in getting working code – especially when debugging in headless mode or connecting to remote browsers. When I started using LLMs to generate automation code, I found myself stuck in a repetitive loop: navigate to the desired page state, copy-paste HTML into the AI chat, and ask it to generate code. The worst part is that there was no easy way to run that generated code without losing the page state, forcing me to restart the browser session constantly. This wasted large amounts of time and mental energy. I built ScrapeCopilot to make this workflow seamless. How it works: ScrapeCopilot combines the power of a Jupyter-style notebook with a live Puppeteer browser session and integrated AI. - Live Interactive Development: When you create an automation notebook, it initiates a fresh Puppeteer browser session. The page object is exposed directly to your notebook cells, allowing you to run any Puppeteer code against the live browser state and see the results instantly. - AI-Powered Assistance: It integrates with GitHub Copilot (via the @scrapecopilot chat participant). The AI automatically sees the current page HTML, allowing it to generate highly relevant Puppeteer code based on your instructions directly within the chat. - LLM Code Export: Once you've developed your automation logic, you can easily export the final, complete Puppeteer script based on your instructions. This tool saves me hours daily, but even more importantly, it improves the developer experience in browser automation which is frustrating area. I believe ScrapeCopilot can complement existing browser automation tools and frameworks by providing an interactive AI-assisted development experience. Current Status & Future Plans: - The extension currently works within VS Code. It will work in Cursor, but without chat support initially. I'm actively working on integrating a backend server to enable full chat functionality with Cursor. - Currently the key workflow assumes that you create a new browser automation step by step, using code cells. But in my work I spend half of the time fixing existing automations, so my focus now is trying to adapt extension for debugging and fixing existing code. - Playwright support is also on the list. Check out short videos: - Demo: Headless False - https://scrapecopilot.ai/assets/demo-headless-false-Dhc_jeNR... - Demo: Headless True - https://scrapecopilot.ai/assets/demo-headless-true-PRQndDxP.... I'd love to hear your thoughts, feedback, and any suggestions!

Share card

Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, new, visual · Missing: mac, agents, macos
93%93% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · 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: video, way · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Si
Sitrep - AI Copilot For Incidents49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Sitrep - AI Copilot For Incidents

Hacker News4
TradeSage
TradeSage69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tradingview AI copilot

Product Hunt+17
Zuni
Zuni13%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI Copilot For Your Browser

Indie Hackerscommitment-full-time
PopAir
PopAir78%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

All-in-one AI Copilot for MacOS

Indie Hackers1$200/moai
PopAir
PopAir91%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your All-in-one AI Copilot for MacOS

Product Hunt+88Productivity
Monira
Monira59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI copilot for your money

Indie Hackers1ai
Memori
Memori48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI notebook

Indie Hackers1ai
Ku
Kubectl Notebook56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Kubectl Notebook

Hacker News12
Qu
Quiver – The Programmer's Notebook59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Quiver – The Programmer's Notebook

Hacker News64
Cocktailicious
Cocktailicious15%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

drinking notebook

Indie Hackers1food-drinks