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AgentQL

AI-powered web scraping and automation made simple.

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October 9, 2024

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AgentQL

Web scraping

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AI-powered web scraping and automation made simple.

Overview

Overview Releases Pricing Reviews Prompts Pros & Cons Q&A Alternatives Recommendations

Web scraping43 0

API automation Web scraping data extraction data scraping Web AutomationFree + from $99/mo

Most popular alternative: Browse AI (361 saves)

View 7 alternatives Recommendations

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AgentQL is an AI-powered tool designed for painless data extraction and web automation. It allows users to build AI agents using natural language queries for precise control over web and app automation tasks.

The tool's core feature is its capability to reliably locate and interact with web elements, even when those elements may change in structure or content.

Instead of using brittle XPath or DOM selectors, AgentQL query language allows users to describe the desired elements in natural language, effectively targeting elements based on their semantic meaning rather than solely on their structure.

The tool also provides the opportunity to automate tasks such as form filling, data scraping, and end-to-end testing, effectively reducing manual effort and enhancing productivity.

Developers can also use natural language instructions to define the exact shape they need the results in, offering better control over the extracted data's output.

To ensure user understanding, the AgentQL system has been built to avoid enigmatic 'AI black box' processes and to be deterministic in its outputs. Using unique API keys, users can secure their access and use the features of AgentQL, providing a secure experience across their applications.

Installation is facilitated by a browser extension and an SDK, enabling users to write AgentQL queries and perform web scraping tasks seamlessly.

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Initial release

August 16, 2024

Initial release of AgentQL.

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Web scraping AgentQL

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AgentQL was manually vetted by our editorial team and was first featured on October 9th 2024.

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Pros and Cons

Pros

Semantic element targeting

Natural language queries

Enhanced control over output

Painless data extraction

Painless web automation

Automates form filling

Automates data scraping

Automates end-to-end testing

Productivity enhancement

Easy installation with extension

Easy installation with SDK

Secured access with API keys

Accessible through browser extension

Clear deterministic outputs

Structured data scraping

Locates changing web elements

Reduces manual effort

Flexible result shaping

Reliable XPath alternative

Precise web automation

App automation capabilities

Scraping without modern web complexities

Automated process for productivity

End-to-end testing streamlining

Boosted analytics and insights

Descriptive element targeting

Unique API keys for security

Encourages developer understanding

Reduce context window issues

Avoids hallucinations during tasks

Semantic-based search differentiator

Offers reusable configurations

Saves time and effort

Easy to use interface

Diverse automation capabilities

Boosts data gathering speed

Removes dependency on DOM selectors

Allows customized data shaping

Supports natural language instructions

Designed for painless automation

Great for app automation tasks

Reliable tool for essential data collection

Secure web scraping experience

Semantic selector for elements

Can mold products in desired shape

Automatically fills up forms

Transparent tool operation

Awards from the tech community

View 43 more pros

Cons

Requires browser extension installation

Dependent on unique API keys

Limited to semantic search

May struggle with complex structures

Lack of XPath, DOM Selectors

Potential language limitations

Requires knowledge of AgentQL language

SDK installation needed

Relies on natural language input

Potential issues with dynamic content

View 5 more cons

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Working great as of 30/11/2024. Let me tell you why I'm so happy about this, because I was desperate: - Firecrawl.dev? Inconsistent API documentation. Apify scrapers? Couldn't work on my target URL. - I spent $150 over 4-5 OTHER tools before finding this one, which is free to use locally right now. Wow. I'm dumb. - My target URL was a broken site, with 500 javascript errors, content violations, bad cookies, etc. - Not a single scraper worked that I tried, except for this one. So yeah, I'd say I'm pretty happy

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dont have option to scrap in bulk, then is useless

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I've been using Octoparse for a few months now, and I must say, it has exceeded my expectations. As someone with limited coding knowledge, I was initially hesitant to try web scraping. However, Octoparse made the process incredibly easy with its intuitive interface and powerful features. I've been able to extract data from multiple websites without any hassle, and the automation capabilities have saved me a ton of time. The customer support team has also been incredibly helpful whenever I've had questions or encountered issues. Overall, I highly recommend Octoparse to anyone looking for a reliable and user-friendly web scraping tool. Another notable aspect of Octoparse is its versatility, catering to both beginners and advanced users alike. Its pre-built templates and workflows streamline the scraping process, while advanced users can leverage its customization options for more complex scraping tasks. Additionally, Octoparse offers scheduling and automation features, allowing users to automate repetitive scraping tasks and save time.

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AVOID AT ALL COSTS. Amateur hour if I ever saw it: they change their entire API endpoints on a whim on the SAME VERSION, breaking all of the work you've done to integrate with them (thousands of $), then tell you you're not an $5k / month Enterprise customer and they don't really support their self serve product so...tough luck buddy. I was one of their first customers and have been using them for over a year and a half only to wake up one day to customer complaints because our integration had broken and be told they basically don't care about. After I reached out to their team, it became clear that they had simply changed their entire API from one day to the next on the same version, with no notice and a documentation that doesn't reflect the changes they made. Literally everything is broken in one way or another: the UI fails to save changes every other try, the API has three different versions in use at the same time, some endpoints use v3 others use v4, similar payload responses don't even reply with the same structure for the data, the documentation is completely out of sync with the actual endpoints, the webhooks trigger 3 times in a row and on and on and on... Somehow they have several engineers, yet no-one there actually knows how to fix your problem. I've been a customer for over a year and a half and after breaking my entire integration, they just told me to go take my business elsewhere because they couldn't support their OWN breaking changes! Oh and by the way, it took a week of back and forth and trying to fix my integration and work with their broken documentation to tell me this. Total insanity. I couldn't ever imagine being an Enterprise customer with these people, their whole product is built on a shoestring and they have absolutely no respect whatsoever for their customers.

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Q&A

What is AgentQL?

AgentQL is an AI-powered tool specializing in data extraction and web automation. It enables users to create AI agents using natural language queries, giving them precise control over web and app automation tasks. Users can use AgentQL to automate tasks such as form filling, data scraping, and end-to-end testing, enhancing productivity by reducing manual effort.

How does AgentQL's web scraping work?

AgentQL's web scraping works by enabling reliable interaction with web elements, even if these elements undergo changes in structure or content. Instead of relying on brittle XPath or DOM selectors, users can describe the desired elements in natural language through the AgentQL query language. This approach lets users target elements based on their semantic meaning, not just their structure.

Does AgentQL require coding skills?

AgentQL does not necessarily require coding skills. It is designed to reduce complexity involved in web data extraction by allowing users to utilise natural language queries. However, developers can explore its potential further by using AgentQL SDK for automating tasks.

What is the core feature of AgentQL?

The core feature of AgentQL is its ability to reliably locate and interact with web elements, even as they change in structure or content. It does this through a natural language query language that allows users to target web elements based on their semantic meaning and not just their structure.

What does the AgentQL query language allow me to do?

With the AgentQL query language, you can describe the desired elements on their website in natural language for efficient targeting of elements. This allows you to target web elements based on their semantic meaning rather than only on their structural attributes. Moreover, you can use natural language instructions to shape the results you need, giving you richer control over the output of the extracted data.

Can AgentQL interact with dynamic web elements?

Yes, AgentQL can interact with dynamic web elements. It is capable of reliably locating and interacting with web elements, even when their structure or content changes. Users describe the desired elements in natural language, effectively targeting elements based on their semantic meaning rather than solely on their structure.

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How can AgentQL automate form filling?

AgentQL automates form filling by using the defined AI agents. Users can describe the necessary steps and data in natural language for these agents to fill the forms automatically. This significantly reduces manual efforts, saves time, and enhances productivity.

What is end-to-end testing in AgentQL?

End-to-end testing in AgentQL is a feature that allows users to ensure the seamless performance of their applications. It is part of the broader automation capabilities of AgentQL that reduce manual effort and enhance productivity.

How can I control the output of the data extracted ?

AgentQL allows you to control the output of the extracted data by providing natural language instructions outlining the exact shape you need the results in. This ensures better control over the output of the extracted data.

How is AgentQL different from other AI black box systems?

AgentQL differs from other AI black box systems by focusing on determinism and transparency. The system avoids enigmatic 'AI black box' processes by making its workings as clear as possible to the user. It has been designed to be straightforward in its outputs.

What is the purpose of the unique API keys in AgentQL?

The unique API keys in AgentQL are used to secure user access. They serve as a gateway to using the powerful features of AgentQL, ensuring a secure experience across your applications.

Is AgentQL secure to use?

Yes, AgentQL is secure to use. User access is encrypted with unique API keys that provide a secure experience across applications. This ensures only authorized access to the powerful features of AgentQL.

How is AgentQL installed?

AgentQL can be installed via a browser extension or an SDK. This facilitates users to write AgentQL queries and perform web scraping tasks seamlessly.

Can I use AgentQL in my browser?

Yes, you can use AgentQL in your browser. You need to install the browser extension, which serves as a gateway to a seamless web scraping experience.

Does AgentQL have a SDK?

Yes, AgentQL does have a software development kit (SDK). The SDK enables users to write AgentQL queries and perform web scraping tasks.

How does natural language processing fit into AgentQL's functionalities?

Natural language processing fits into AgentQL's functionalities by allowing users to describe the target elements in natural language. This enables them to perform tasks such as web scraping and data extraction with precise control, integrating an intuitive and user-friendly approach to web and app automation.

What role does semantic search play in AgentQL's web scraping?

Semantic search plays a crucial role in AgentQL's web scraping by enabling it to locate web elements based on their meaning. Instead of relying on brittle XPath or DOM selectors, AgentQL uses semantic search to enable users to target search elements based on their semantic meaning and not only their structural attributes.

What are some applications of AgentQL?

Applications of AgentQL span across data scraping, web automation, and E2E testing. It can be used to quickly gather essential data, boost analytics and insights, reduce manual effort and enhance productivity with automated processes, and streamline testing to ensure seamless performance of applications.

Where can I get help and support for AgentQL?

Help and support for AgentQL can be found on their website. The company also provides a supportive community where users can join their Discord channel for discussions, insights, and shared experiences of using AgentQL.

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