Cross-site data extraction
Reuse one semantic schema across sites that expose similar products, listings, profiles or records with different markup.
Independent tool overview
AgentQL at a glance
AgentQL is an AI-powered query language and developer platform for extracting structured web data and locating elements for browser automation. Instead of brittle CSS or XPath selectors, developers describe the content or control they want and receive typed JSON or Playwright locators. It is useful for cross-site data workflows and changing interfaces, provided teams still validate every result and respect site access rules.
Visit the official AgentQL site ↗
- Best for
- Resilient web extraction and browser automation
- Core approach
- Natural-language semantic selectors
- Outputs
- Structured JSON or Playwright locators
- Interfaces
- Python, JavaScript, REST API and Chrome debugger
- Browser runtime
- Local Playwright or managed remote sessions
- Provider
- TinyFish
Overview
What AgentQL is
An AgentQL query resembles a small schema: name a single field, a list or nested fields, and optionally add a plain-language description. The service interprets the page semantically and returns data in the requested shape. For automation, the same approach returns elements that can be clicked, filled or otherwise controlled through Playwright.
Developers can use Python and JavaScript SDKs, a REST API, a Chrome debugger and AgentQL's managed remote browsers. The REST API can query public URLs, supplied HTML, PDFs and images, while remote sessions provide CDP access, streaming and configurable browser profiles.
Semantic selectors reduce maintenance but do not remove test engineering. A page can contain ambiguous labels, stale content, bot defenses or a redesigned user flow that is semantically similar but operationally wrong. Production automations need schema validation, assertions, screenshots, retries, rate limits and human approval before consequential actions.
Use cases
Who AgentQL is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Changing web interfaces
Reduce maintenance when DOM structure, class names, A/B tests or minor layouts change frequently.
Playwright automation teams
Add natural-language element discovery while keeping explicit browser steps, assertions and error handling in code.
Agent developers
Give an agent structured page data or element handles without sending entire pages through a custom LLM parsing pipeline.
Capabilities
Core AgentQL features
Semantic query language
Describe desired fields and elements with readable names, nested structure, lists and optional contextual prompts.
Structured data extraction
Return JSON shaped by the query, including type hints for fields such as integers and nested collections.
Playwright element lookup
Convert semantic queries or one-off prompts into locators that a Python or JavaScript automation can interact with.
REST document and page API
Query URLs, raw HTML, PDFs and images through HTTP from languages that do not use the native SDKs.
Remote browser sessions
Allocate managed browsers with CDP connectivity, page streaming, user-agent presets, profiles and concurrency.
Debugger and playground
Test and inspect AgentQL queries in Chrome DevTools or an online playground before putting them into code.
Process
How the AgentQL workflow works
Step 1
Define an output contract
Write the exact fields, types, required values and acceptable null behavior before choosing the semantic query.
Step 2
Prototype in the debugger
Test representative pages, ambiguous elements, lists and contextual descriptions with the Chrome extension or playground.
Step 3
Choose local or remote browsing
Use local Playwright when infrastructure and sessions are controlled; use remote browsers when managed concurrency or CDP streaming is valuable.
Step 4
Add deterministic validation
Check URLs, counts, types, values, page state and screenshots before accepting data or performing the next action.
Step 5
Handle access and change
Respect site terms, robots guidance, authentication boundaries and rate limits; add retries and alerts for changed page semantics.
Step 6
Monitor cost and quality
Track API calls, browser hours, null rates, schema failures, incorrect matches and manual-review volume by workflow.
Cost
AgentQL pricing and free plan
AgentQL bills API calls and managed remote-browser time separately. The trial includes 300 API calls and one remote-browser hour. Starter has no monthly fee but moves to usage overages after its allowances; Professional bundles larger call, browser-hour, rate-limit and concurrency allocations. Prices below were reviewed on August 29, 2026.
Free trial
$0; no credit card required
A one-time evaluation allowance with full developer tools.
- 300 API calls
- 10 API calls per minute
- 1 managed remote-browser hour
- 1 concurrent remote-browser session
Starter
$0/month plus usage
For developers building smaller agents and data workflows.
- 50 API calls per month, then $0.02 per call
- 10 API calls per minute
- 10 remote-browser hours included, then $0.12 per hour
- 5 concurrent remote-browser sessions
Professional
$99/month
For regular data pipelines and web automations.
- 10,000 API calls per month, then $0.015 per call
- 50 API calls per minute
- 500 remote-browser hours included, then $0.10 per hour
- 100 concurrent remote-browser sessions and priority email support
Enterprise
Custom pricing
For managed datasets, dedicated infrastructure and organizational support.
- Ready-to-use datasets and managed solutions
- Dedicated cloud environment
- On-premise deployment available
- 24/7 premium support and dedicated account management
Pricing checked . Check current pricing at the source ↗
Assessment
AgentQL strengths and limitations
Where it stands out
- Semantic selectors can survive markup and layout changes that break CSS and XPath selectors.
- One readable query defines both the desired fields and the output structure.
- Supports data extraction and element interaction rather than forcing separate tools.
- Works with existing Playwright concepts and local browsers.
- REST access covers web pages, HTML, PDFs and images.
- Managed browser sessions provide useful concurrency and streaming without separate infrastructure.
- Debugger, playground and generous trial make query design easy to evaluate.
What to consider
- Semantic matching can choose a plausible but incorrect field or element when labels and context are ambiguous.
- The same natural-language query may need additional context across sites with different business meanings.
- Self-healing selectors do not protect against redesigned workflows, authentication changes, CAPTCHAs or unavailable data.
- API calls and managed-browser hours are separate usage meters and both can grow at scale.
- Remote browser overage and concurrency must be monitored independently from query volume.
- Automating logged-in pages creates credential, session and personal-data handling obligations.
- Website terms, robots directives, copyright, privacy law and rate limits still apply to extracted content.
- Consequential clicks, submissions and purchases require deterministic safeguards and approval rather than semantic selection alone.
Compare
AgentQL alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Business Operations
Gumloop
A visual no-code automation platform for teams that want broader workflow orchestration without writing Playwright scripts.
Explore Gumloop →Business Operations
Bardeen
A browser-centered automation option for business users building repeatable workflows with less developer infrastructure.
Explore Bardeen →Agents
Gemini Computer Use
A computer-use model for agent developers who want model-driven interface control rather than a specialized semantic query layer.
Explore Gemini Computer Use →Questions
AgentQL FAQs
What is AgentQL?
AgentQL is an AI-powered query language and developer platform that finds web data and interface elements by semantic description instead of fixed DOM selectors.
Is AgentQL a scraping tool or an automation tool?
It is both. It can return structured page data for scraping or Playwright locators that a script uses to click, type and navigate.
Does AgentQL use Playwright?
Yes. Its Python and JavaScript SDK workflows wrap Playwright pages, while remote browser sessions expose CDP for compatible browser control.
Can AgentQL query PDFs and images?
Yes. The REST API includes document querying for PDFs and image files in addition to URLs and supplied HTML.
How much does AgentQL cost?
Starter is $0 monthly with 50 included API calls and 10 remote-browser hours, followed by per-call and per-hour charges. Professional is $99 monthly.
What is included in the AgentQL free trial?
The trial includes 300 API calls, one managed-browser hour, 10 calls per minute and one concurrent remote-browser session.
Are AgentQL selectors deterministic?
AgentQL markets consistent structured results, but semantic interpretation still needs assertions and monitoring because real pages and meanings can change.
Can AgentQL work behind a login?
Its SDK can operate on authenticated browser pages, but the implementer is responsible for authorized access, secure credential handling and the target site's rules.
Does AgentQL bypass website restrictions?
It offers browser profiles, proxies and stealth-related guidance, but those capabilities do not grant permission to ignore access controls, terms, robots rules or applicable law.
Bottom line
Our AgentQL verdict
AgentQL is a strong fit when selector maintenance is the expensive part of a web data or Playwright workflow. Its compact schemas and semantic element lookup can reduce glue code across changing pages. Treat it as a probabilistic discovery layer inside a deterministic system: validate outputs, constrain actions, monitor two separate usage meters and obtain authorization for every site and account automated.
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