AgentQL
AI-powered query language for web scraping and automation with natural language.
Pricing
About AgentQL
AgentQL is an AI-powered query language and automation suite that enables developers to extract data from websites using natural language instead of fragile XPath or CSS selectors. Built by TinyFish, it connects large language models and AI agents to the web through a unified interface that understands page structure semantically. The tool works across any website—public, private, or behind authentication—and returns structured data consistently despite dynamic content changes. Developers, data engineers, and AI teams use AgentQL to build web automation workflows that are more resilient and maintainable than traditional parsing scripts. The platform supports multiple SDK languages (Python and JavaScript), offers a browser-based debugger for query optimization, and provides a REST API for server-side data extraction. A notable limitation is that advanced use cases may require understanding of both the query language syntax and proper prompt engineering to achieve optimal results.
At a glance
- Company
- TinyFish
- Platforms
- Web, Python, JavaScript, REST API, Chrome Extension
- API
- Available
- Integrations
- LangChain, Playwright
- Last verified
- June 2026
Who It's For
- •AI and machine learning engineers building AI agents
- •Developers creating web automation tools
- •Data engineers and analysts performing web scraping
- •Teams building data workflow pipelines
- •Businesses needing reliable web data extraction
How It Works
- 1User defines the data structure they want using natural language queries (e.g., { products[] { product_name product_price } })
- 2AgentQL's AI analyzes the webpage structure to identify and locate the requested elements semantically
- 3The query language parser processes the page and extracts data in the specified format
- 4Results are returned as structured JSON data
- 5Self-healing mechanism automatically adjusts when page structure changes or content is dynamic
How to Use AgentQL
- 1Sign up for a free account (300 free API calls for trial)
- 2Write a natural language query describing the data you want to extract
- 3Use the REST API, Python SDK, or JavaScript SDK to execute queries
- 4Optionally use the browser extension debugger to test and optimize queries on live pages
- 5Integrate with your workflow using SDKs or API endpoints
Key Features
- •Natural language query language (no XPath or CSS selectors needed)
- •Python and JavaScript SDKs
- •REST API with browserless execution
- •Browser-based debugger extension for query optimization
- •Self-healing queries that adapt to page changes
- •Structured JSON output
- •Support for authentication behind login pages
- •PDF parsing capabilities
- •Playwright integration for headless browser automation
- •Reusable queries across similar pages
Use Cases
- •E-commerce product data extraction with pricing and descriptions
- •Job board scraping and aggregation
- •Social media data collection and analysis
- •Web automation and workflow orchestration for AI agents
- •PDF parsing for extracting structured information like tables
Pros & Cons
Advantages
- •Eliminates fragile selector maintenance by using AI-powered semantic understanding of page structure
- •Works consistently across similar pages without code changes due to self-healing queries
- •Multiple integration options (REST API, Python/JavaScript SDKs, LangChain) for flexible deployment
- •Ranked #1 Product of the Day and Week on Product Hunt, indicating strong market validation
Disadvantages
- •Free tier limited to 300 API calls for trial, requiring paid plans for regular use
- •Pricing for API calls ($0.02 per call on Starter, $0.015 on Professional) can accumulate for high-volume scraping
- •Requires learning a new query language syntax, adding adoption friction compared to direct DOM/CSS approaches
Alternatives
See all AgentQL alternatives →Related Tools
View All Tools
AI-Flow
Connect and chain multiple AI models to build automated workflows.
CopilotKit
Enterprise frontend stack for building AI agent interfaces in applications.
Daytona
Secure infrastructure for safely running AI-generated code in milliseconds.
Sutro
Production-grade backends for platforms using a new data model language.
Midjourney API for AI Image Generation - Apiframe
Unified API for accessing multiple AI media generation models.
Blumix
All-in-one AI toolkit merging with Bleenk platform.
Reviews for AgentQL
Based on 0 reviews
Rating Distribution
No Reviews Yet
Be the first to share your experience with AgentQL!
Frequently Asked Questions
What is AgentQL?
AgentQL is an AI-powered query language and automation suite that enables developers to extract data from websites using natural language instead of fragile XPath or CSS selectors. Built by TinyFish, it connects large language models and AI agents to the web through a unified interface that understands page structure semantically.
How much does AgentQL cost?
AgentQL is free to use. A free trial is available.
Is AgentQL free?
Yes, AgentQL offers a free plan you can start with.
What are the best AgentQL alternatives?
Popular AgentQL alternatives include Firecrawl, PaioClaw, Baby AGI.
What is AgentQL used for?
AgentQL is commonly used for E-commerce product data extraction with pricing and descriptions, Job board scraping and aggregation, Social media data collection and analysis.
Does AgentQL have an API?
Yes, AgentQL offers an API for developers.
What platforms does AgentQL support?
AgentQL is available on Web, Python, JavaScript, REST API, Chrome Extension.
Information Accuracy
Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.