Review official docs
Back to Tools
sdk ยท tool profile
Agentql
AgentQL is a suite of tools for connecting your AI to the web. Featuring a query language and Playwright integrations for interacting with elements and extracting data quickly, precisely, and at scale. Includes REST API, Python and JavaScript SDKs, browser debugger.
automation
01
At a glance.
A compact read before the deeper capability notes and official setup links.
02
Core features.
Feature cards focus on what the tool helps users do, not generated setup commands.
AgentQL connects LLMs and AI agents to the entire web
AgentQL is a suite of tools for extracting data and automating workflows on live web sites featuring an AI-powered query language, Python and JavaScript SDKs, a browser-based debugger, and a REST API endpoint.
AgentQL's natural language selectors find elements intuitively based on the content of the web page and work across similar web sites, self-healing as UI changes over time.
Playwright AgentQL's Python SDK and JavaScript SDK seamlessly integrates with Playwright for advanced automation and testing.
Python SDK for running automation and scraping scripts with AgentQL queries in Python.
JavaScript SDK for running automation and scraping scripts with AgentQL queries in JavaScript.
Integrations with agent frameworks and automation tools like Langchain and Zapier and our MCP server.
Debugger Browser Extension lets you debug and finesse queries in real-time on live sites.
04
Agent / Skill / MCP / Workflow fit.
This panel keeps technical format separate from the user-facing AI category.
05
Official setup path.
Generated install snippets are intentionally not mirrored here because they drift. The page links to source-owned setup docs instead.
06
Evidence and adoption notes.
These notes help a user decide whether to investigate the official project further.
Source repository last pushed at 2026-05-12T06:01:45Z.
Generated from source metadata; confirm operational details in the official project before adopting it.
Review the upstream license, maintenance activity, and issue history before using it in production.
Trusted source