AgentQL Introduction
AgentQL is an AI-powered query language and tool for reliable web element location and data extraction using natural language-like syntax.
View MoreWhat is AgentQL
AgentQL is a flexible and intuitive query language designed to simplify web automation and data scraping. Developed by Tiny Fish Inc., it allows developers to locate web elements and extract data using natural language queries instead of complex DOM structures or fragile XPath expressions. AgentQL consists of a query language, Python SDK, Chrome extension for debugging, and supporting developer tools to enable programmatic access to web content.
How does AgentQL work?
AgentQL works by allowing users to write structured queries specifying the web elements or data they want to interact with or extract. These queries use a schema-less, natural language-like syntax to describe the desired elements. The AgentQL system then processes these queries along with the HTML of the target webpage, using AI to reliably locate the specified elements even as websites change. The AgentQL SDK provides methods to interact with the identified elements, such as clicking or filling form fields. For data extraction, AgentQL can return results in a specified shape, making it easy to process the scraped information.
Benefits of AgentQL
The key benefits of AgentQL include its reliability in locating web elements even as websites change, eliminating the need for fragile XPath or DOM selectors. Its natural language-like syntax makes it intuitive and easy to use, reducing the learning curve for developers. AgentQL offers flexibility in specifying exactly what data to extract and in what format, streamlining the data scraping process. It also provides tools for debugging and testing queries in real-time, enhancing development efficiency. Overall, AgentQL simplifies web automation and data extraction tasks, making them more accessible and less error-prone for developers and researchers.
AgentQL Monthly Traffic Trends
AgentQL experienced a significant 49.2% decline in traffic, reaching 30.8K visits. Despite positive mentions in recent news, the lack of notable product updates or new features might have contributed to the drop. Additionally, the increasing focus on autonomous AI agents and competitor activities could have diverted user attention.
View history traffic
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