AgentQL API
Browse all Agentql APIs★ Only Publicly Available OpenAPI DocumentAI/MLMl InferenceapiKey8 EndpointsREST
For Agents
Extract structured fields from any web page using natural language or AgentQL queries. Run inside Tetra remote browser sessions when sites require interaction or login.
Use for: I need to extract product prices from an e-commerce listing page, Get the headline and author from a news article URL, Find all job postings on a careers page and return them as a list, Set up a Tetra browser session to log in and scrape behind authentication
Not supported: Does not handle proxy rotation, CAPTCHA solving, dataset storage, or large-scale crawl scheduling — use for structured extraction from individual URLs only.
Jentic publishes the only available OpenAPI specification for AgentQL API, keeping it validated and agent-ready. AgentQL extracts structured data from web pages and documents using AgentQL query syntax or natural language prompts. The 0.1.0 spec exposes both versioned (/v1) and unversioned routes for the query-data endpoint plus the Tetra remote Chrome browser session API. Each call returns parsed fields keyed by the names declared in the query, removing brittle CSS or XPath selectors from agent code.
Install Jentic One Beta
Connect the AgentQL API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the AgentQL API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with AgentQL API.
Query structured fields from public web pages without writing CSS or XPath selectors
Run AgentQL queries inside a Tetra remote browser session for sites that require login or JavaScript interaction
Use natural language prompts as an alternative to AgentQL syntax for ad-hoc extraction tasks
Track API key usage and remaining quota with the /v1/usage endpoint
Capture per-session Tetra usage to reconcile browser-time costs with /v1/tetra/usage
Use Cases
Patterns agents use AgentQL API for, with concrete tasks.
★ Web Data Extraction Without Selectors
Replace brittle CSS-selector scrapers with semantic AgentQL queries that survive site redesigns. The agent posts a query to /v1/query-data with the target URL, and AgentQL returns named fields matching the query shape. Suited to monitoring product catalogs, news feeds, or directory pages where layout changes frequently.
Call POST /v1/query-data with url='https://news.ycombinator.com' and query='{ stories[] { title link } }' and return the parsed stories array
Authenticated Page Scraping via Tetra
Use a Tetra remote browser session to log into a SaaS dashboard, navigate to a report page, and run an AgentQL query to extract the table. The agent calls POST /v1/tetra/sessions to provision the session, drives the browser, and then issues query-data calls scoped to the session. Useful for pulling reports from internal tools that have no public API.
Create a Tetra session, sign in to a vendor dashboard with stored credentials, then run a query-data extraction against the analytics page
Document Field Extraction
Pass PDF or image URLs to AgentQL with a natural-language prompt to pull invoice numbers, totals, or contract terms into a structured object. The agent does not need to run OCR or build per-template parsers — AgentQL returns the named fields directly. Suited for processing supplier invoices or scanned forms at moderate volume.
Submit a PDF invoice URL with the prompt 'extract invoice_number, total_amount, due_date' and store the parsed fields in the accounting system
Agent-Driven Research Workflows
Let a Jentic-connected agent decide on the fly which URLs to query and what fields to extract during a research task. The agent searches Jentic for the AgentQL query operation, loads the input schema, and issues queries iteratively as it explores links. This replaces hand-coded scraping pipelines for one-off research jobs.
Given a competitor's homepage URL, recursively query for product pages and extract pricing into a comparison table
Key Endpoints
8 endpoints — jentic publishes the only available openapi specification for agentql api, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/v1/query-data
Run an AgentQL query against a URL
POST
/v1/tetra/sessions
Create a remote browser session
GET
/v1/usage
Get account API usage
GET
/v1/tetra/usage
Get Tetra session usage
POST
/v1/query-data
Run an AgentQL query against a URL
POST
/v1/tetra/sessions
Create a remote browser session
GET
/v1/usage
Get account API usage
GET
/v1/tetra/usage
Get Tetra session usage
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
AgentQL API keys are stored encrypted in the Jentic vault. The X-API-Key header is injected at execution time so the raw key never enters the agent context or chat logs.
Intent-based discovery
Agents search by intent (e.g. 'extract data from a web page') and Jentic returns the AgentQL query operations with their input schemas and accepted query syntax.
Time to first call
Direct AgentQL integration: a few hours for auth, query construction, and Tetra session lifecycle. Through Jentic: under 15 minutes — search, load, execute.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using AgentQL API through Jentic.
Why is there no official OpenAPI spec for AgentQL API?
AgentQL does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call AgentQL API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the AgentQL API use?
AgentQL uses an API key passed in the X-API-Key request header. Through Jentic the key is held in the credential vault and injected at execution time, so the raw key never enters the agent's context window.
Can I scrape sites that require a login with the AgentQL API?
Yes, via the Tetra remote browser. POST /v1/tetra/sessions to provision a Chrome session, drive it to the login flow, then issue /v1/query-data calls scoped to that session id. Static-page queries against /v1/query-data alone do not handle authentication.
What are the rate limits for the AgentQL API?
AgentQL enforces per-plan request and Tetra-minute quotas. Call GET /v1/usage to read the current period's consumption. The API does not document a fixed requests-per-second limit; build retry-with-backoff for any 429 response.
How do I extract a structured product list from a URL through Jentic?
Use the Jentic search query 'extract structured data from a web page'. Jentic returns the POST /v1/query-data operation; load its schema, supply the url and an AgentQL query like '{ products[] { name price } }', and execute. The response contains the parsed products array.
Does AgentQL support natural-language extraction without writing AgentQL syntax?
Yes. The /v1/query-data endpoint accepts a prompt parameter as an alternative to a structured query. The result is still returned as JSON, but the field shape is inferred from the prompt rather than declared explicitly.
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