AgentQL

What does AgentQL do?

AgentQL turns web pages into structured outputs by letting developers describe the data they want with queries instead of brittle XPath or DOM/CSS selectors. Its Python and Node.js SDKs, browser-based debugger, and browserless REST API work together to extract data, automate interactions, and support E2E testing across public or private pages, including authenticated sites. The same query can be reused across similar layouts, and the system is designed to keep results deterministic as pages change. At scale, AgentQL is built for web automation and data workflows rather than one-off scraping. It supports both headless browser flows and direct API retrieval, plus PDF parsing for difficult documents like tables. The product page shows use across e-commerce, job boards, and social media, and the company says thousands of developers use its tools. Customer examples shown on the site include Heal.dev and Hove, while the integrations page connects AgentQL with tools like Zapier, Langflow, and LangChain.

Why use AgentQL?

• AgentQL replaces fragile selector logic with semantic queries, so teams can keep workflows working when page structure shifts.
• Its browser extension debugger lets developers tune queries in real time on any page instead of iterating blindly.
• The browserless REST API supports data retrieval without a browser, which simplifies lighter-weight automation paths.
• Reusable queries across similar pages reduce rework when you need the same extraction pattern at scale.
• On-premise deployment is available for teams that need tighter control over where data processing runs.

Who is AgentQL for?

• Python developers who need structured web extraction without brittle selectors.
• Node.js developers who want reusable queries for automation and testing.
• Data engineers who need consistent outputs from changing website layouts.
• AI builders who want web pages turned into agent-ready data.
• Teams using no-code or orchestration tools who need web data in their workflows.

What are AgentQL's key features?

What does AgentQL integrate with?

• Playwright
• Langflow
• AgentStack
• Zapier
• Langchain
• Dify
• GitHub

What are AgentQL's use cases?

How does AgentQL work?

1. Connect your first page in the Versatile SDK or Browserless flow, then point AgentQL at the target site you want to read. Start with a page that matters to your workflow.
2. Describe the fields you need with natural language queries or semantic selectors, and let AgentQL map them to the page structure. Use Works on any page to handle different layouts.
3. Run the Browser-based debugger to inspect results, refine queries, and confirm the output shape before you automate. Check Structured data and Deterministic results as you iterate.
4. Send the same query through the data extraction API or free data collection API in your app, script, or workflow tool. Reuse the query across jobs with Reusable code.
5. Scale extraction with Self-healing and Robustness so page changes break less often. Add PDF parsing or web automation when your workflow needs documents or browser actions too.

How much does AgentQL cost?

Frequently asked questions