LLM Scraper — AI Agent Review & Live Stats

Live GitHub stats, community sentiment, and trend data for LLM Scraper. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Mar 27, 2026 • Sentiment updated: Mar 16, 2026

GitHub Statistics

Community Sentiment

Community Buzz: The community is actively engaged with the project, with many contributors and a high number of commits. The project's focus on browser automation and LLM scraping is well-received. Users appreciate the project's use of popular technologies like Playwright and LangChain.

Why LLM Scraper Stands Out

LLM Scraper stands out from alternatives by providing a unique combination of LLM-based data extraction and Playwright-based browser automation. Its support for multiple LLM models, including GPT, Sonnet, and Llama, makes it a versatile tool for various use cases. The project's use of Zod and JSON Schema for schema definition ensures full type-safety with TypeScript. Additionally, its streaming mode and code-generation features make it an attractive choice for developers looking to build scalable and efficient data extraction pipelines.

Built With

Build a web data extraction pipeline — LLM Scraper enables it by providing a TypeScript library to extract structured data from any webpage using LLMs, Build an automated news aggregator — LLM Scraper allows you to define schemas to extract contents into and run the scraper on web pages, Build a research assistant that extracts insights from academic papers — LLM Scraper supports multiple LLM models and provides a streaming mode for partial object streams, Build a price comparison tool for e-commerce websites — LLM Scraper can handle various formatting modes, including html, markdown, and custom formats, Build a social media monitoring tool that tracks brand mentions — LLM Scraper provides a code-generation feature to generate re-usable playwright scripts

Getting Started

  1. Install the required dependencies using `npm i zod playwright llm-scraper`
  2. Initialize your LLM provider using `npm i @ai-sdk/openai` and `const llm = openai('gpt-4o')`
  3. Create a new scraper instance using `const scraper = new LLMScraper(llm)`
  4. Define a schema to extract contents into using `const schema = z.object({ ... })`
  5. Try running the scraper using `const { data } = await scraper.run(page, Output.object({ schema }), { format: 'html' })` to verify it works

About

Turn any webpage into structured data using LLMs

Category & Tags

Category: data

Tags: ai, artificial-intelligence, browser, browser-automation, gpt, gpt-4, langchain, llama, llm, openai, playwright, puppeteer, scraper

Market Context

The project is part of the growing trend of using AI and LLMs for web scraping and automation, with potential applications in data analysis and business intelligence.