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agentql

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Basic Information

AgentQL is a developer-focused suite of tools for extracting data and automating workflows on live websites using an AI-powered query language. It provides Python and JavaScript SDKs, a REST API endpoint, a browser debugger extension, and integrations with Playwright to let code and agents interact with public and private pages, including behind authentication and dynamically generated content. AgentQL lets users write natural language queries that locate page elements by meaning rather than brittle selectors, define structured output shapes, and apply transforms to extracted data. The project includes a playground for experimenting with queries and exporting scripts as well as example scripts and Colab notebooks demonstrating common automation scenarios. It is intended to connect LLMs and AI agents to the web and to simplify building robust web-capable agents.

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App URL
https://github.com/tinyfish-io/agentql
Github Repository
https://github.com/tinyfish-io/agentql/blob/main/README.md

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App Details

Features
AgentQL includes an AI-driven query language with natural language selectors that find elements by content and context. SDKs are available for Python and JavaScript with Playwright integration for advanced automation and testing. A REST API allows executing queries without an SDK. The tool supports structured output and in-query transforms, cross-site compatibility so the same query can work across similar sites, and resilience to UI changes for long-lived automation. Supporting tooling includes a browser debugger extension for live query tuning, a web playground to craft and export scripts, and integrations with agent frameworks and automation platforms. The repository contains many example scripts covering login, pagination, headless and remote browsers, anti-bot behavior, and common scraping tasks.
Use Cases
AgentQL lowers the barrier to building web-aware agents and automation by letting developers express data targets in natural language rather than fragile selectors. It helps teams collect structured data from dynamic and authenticated pages, maintain queries that tolerate UI changes, and reuse queries across similar sites. The SDKs, REST API, and Playwright support enable embedding AgentQL into scripts, services, or agent frameworks. Included examples speed up common tasks such as closing popups, paginated scraping, e-commerce pricing collection, sentiment analysis, saving auth sessions, and running in Colab. The debugger and playground make iterative query development easier, and integrations with tools like Langchain and Zapier enable orchestration with broader automation and multi-agent setups.

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