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What is AgentQL?

AgentQL is a suite of AI-powered tools designed to connect large language models (LLMs) and AI agents to the entire web, enabling efficient and precise data extraction from any webpage. Developed to solve the challenges of fragile web scraping methods like XPath and CSS selectors, AgentQL uses AI to analyze page structures and deliver robust, self-healing queries that adapt to dynamic content changes. It offers a versatile SDK compatible with Python, JavaScript, and Playwright, along with a browser-based debugger for real-time query optimization. The tool supports public and private sites, including those behind authentication, and can parse complex data formats such as tables in PDFs. AgentQL is ideal for developers, data engineers, and teams automating web data workflows, providing reusable code and scalable API access to streamline web automation and data extraction tasks.

AI Tool Review Summary

Performance Score

4.7/5

Content/Output Quality

Accurate, reliable, and adaptable

Interface

Developer-focused with intuitive debugging tools

AI Technology
LLMNLP
Purpose of Tool

To enable AI agents and developers to extract structured data from any web page efficiently and reliably.

Compatibility

Supports Python, JavaScript, Playwright SDKs, REST API, and integrates with various web automation workflows.

Pricing

Freemium with tiered paid plans based on API usage and remote browser hours

Features

Features with the highest value for users are highlighted here.

AI-powered web data extraction

Versatile Python and JavaScript SDKs

Browser-based debugging extension

Self-healing query capabilities

Support for authenticated and dynamic pages

Reusable query configurations

Browserless REST API access

PDF content parsing

How It Works

1

Define Your Query

Write AgentQL queries to specify the structured data you want to extract from web pages.

2

Use SDK or API

Integrate the queries into your applications using Python, JavaScript SDKs, or the REST API.

3

Debug and Optimize

Use the browser-based debugger extension to test and refine queries in real time on any webpage.

4

Automate and Scale

Run queries at scale with remote browser sessions and manage workflows with reusable, self-healing code.

Who Is It For?

Web Developers

Data Engineers

AI Researchers

Automation Specialists

Startups

Enterprise Teams

Product Managers

Content Aggregators

AI Developers

Technical Consultants

Pricing

Starter

$0/monthly
  • 50 free API calls per month
  • 10 API calls per minute
  • 10 hours of remote browser usage
  • 5 concurrent remote browser sessions
  • Community and email support
  • Full access to developer tools
Popular

Professional

$99/monthly
  • 10,000 API calls per month included
  • 50 API calls per minute
  • 500 hours of remote browser usage
  • 100 concurrent remote browser sessions
  • Priority email support
  • Community support
  • Full access to developer tools

Enterprise

Custom/custom
  • Fully managed dedicated cloud environment
  • On-premise deployment available
  • 24/7 premium support
  • Dedicated account manager
  • Ready-to-use datasets
  • Fastest time to market

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Pros & Cons

Pros

  • Robust and reliable alternative to fragile selectors like XPath and CSS.
  • Supports complex workflows with reusable and self-healing queries.

Cons

  • May require learning the custom query language for optimal use.
  • Pricing can be a consideration for heavy usage beyond free tiers.

FAQs

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Reviews

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Rating

5.0

Pros

Cons

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Analytics of Query Mozilla Support with AI Agents | AgentQL

Website traffic and keyword analysis.

Live dataFeb 2026 – Apr 2026

Monthly visits

19.3K

-19.5% vs prior month

Avg. visit duration

00:00:15

M 4 2026 snapshot

Pages / visit

1.74

M 4 2026 snapshot

Bounce rate

39.87%

Lower is better

All traffic · Worldwide

Weekly estimate · Feb 1, 2026 – Apr 29, 2026

3.86K4.14K4.42K4.7K4.98KFeb 1Feb 15Mar 1Mar 15Mar 29Apr 8Apr 22Apr 29

Peak week: 4.98K (Feb 1, 2026)Low week: 3.86K (Apr 1, 2026)WoW: 0.0%Derived from monthly estimates · SimilarWeb-equivalent

Release History

0 releases published

No releases yet.

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