21:I[4606,["9139","static/chunks/9139-29aac3297803e837.js","5162","static/chunks/5162-971519dd5e179b15.js","1163","static/chunks/app/%5Blocale%5D/(with-footer)/ai/%5BwebsiteName%5D/page-93c09f9a3f0813c2.js"],""] 23:I[1895,["9139","static/chunks/9139-29aac3297803e837.js","5162","static/chunks/5162-971519dd5e179b15.js","1163","static/chunks/app/%5Blocale%5D/(with-footer)/ai/%5BwebsiteName%5D/page-93c09f9a3f0813c2.js"],""] 22:T61b,

What is AgentQL?

AgentQL is a suite of tools designed to connect Large Language Models (LLMs) and AI agents to web data, enabling precise automation through natural language queries. It features a query language and parser for interacting with web elements and extracting data quickly, precisely, and at scale. AgentQL also offers versatile SDKs for interacting with web page elements via Playwright and Python/JavaScript, along with a browser-based debugger for optimizing queries in real time.

How to use AgentQL?

Users can start by signing up for a free trial to explore the Playground. They can then use AgentQL's query language to define the data they need from web pages. The platform provides SDKs and a browser extension to interact with and debug queries in real time.

AgentQL's Core Features

Natural language queries for web data extraction

Query language and parser

Playwright integration

Python and JavaScript SDKs

Browser-based debugger

REST API for browserless data retrieval

PDF parsing

AgentQL's Use Cases

#1 E-commerce data extraction

#2 Job board scraping

#3 Social media monitoring

#4 Web automation

#5 Data workflows

#6 Simple automation

AgentQL

📋Introduction

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