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APIs / AI/ML / Agentql / AgentQL API
AgentQL API logo

AgentQL API

Browse all Agentql APIs
★ Only Publicly Available OpenAPI DocumentAI/MLMl InferenceapiKey3 EndpointsREST

For Agents

Query any web page or document with AgentQL syntax or natural language and get structured fields back; spin up a Tetra browser session for authenticated targets.

Use for: Extract product titles and prices from a marketplace page, Get the issue date and total from a PDF invoice URL, Find the social links on a company contact page, Set up a remote browser session to log in and scrape a SaaS dashboard

Not supported: Does not handle proxy rotation, CAPTCHA solving, scheduled crawling, or dataset persistence — use for AgentQL-style structured extraction from URLs and documents only.

Jentic publishes the only available OpenAPI specification for AgentQL API, keeping it validated and agent-ready. The main 1.0.0 surface combines AgentQL's web and document extraction with Tetra remote browser session creation behind a single base URL. Three endpoints handle the full flow: query a web page, query a document, or spin up a browser session for sites that need login. Each query call accepts AgentQL syntax or a natural-language prompt and returns parsed fields directly.

Jentic One on GithubView OpenAPI Document

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 | sh
2

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 instance

Jentic 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.

Run AgentQL queries against URLs to extract named fields without selectors via POST /query-data

Pull invoice and contract fields out of PDFs and images via POST /query-document

Provision a Tetra remote Chrome session via POST /tetra/sessions for authenticated scraping

Substitute natural-language prompts for AgentQL syntax when ad-hoc extraction is faster

Issue scoped queries inside an existing browser session for multi-step authenticated workflows

Use Cases

Patterns agents use AgentQL API for, with concrete tasks.

★ Selectorless Web Extraction

Skip CSS or XPath maintenance by sending AgentQL queries to /query-data alongside the target URL. The API returns parsed fields keyed by the query, surviving most layout changes. Suited to monitoring product, news, and directory pages where DOM churn breaks traditional scrapers.

POST /query-data with url='https://example.com' and query='{ headlines[] { title link } }' and return the parsed list

Document Intelligence

Parse PDFs and images into structured data without per-template OCR pipelines. POST /query-document with a file URL and either an AgentQL query or a natural-language prompt naming fields like invoice_number, total_amount, and due_date. Best for accounts payable, contract intake, and form processing at moderate volume.

POST /query-document with a PDF URL and prompt 'extract supplier_name, invoice_number, total_amount, due_date'

Authenticated Browser Workflows

Use POST /tetra/sessions to provision a Chrome session, drive it through a login, then issue /query-data calls scoped to the session. This unlocks data behind sign-in walls without managing your own headless browser infrastructure.

Create a Tetra session, sign in to a vendor portal, then query for the latest report table on the dashboard

Agent Tool for Live Web Lookups

Connect a Jentic-managed agent to the AgentQL main surface and let it decide when to query a page during a longer plan. The agent searches Jentic for the AgentQL query operation, loads the input schema, and issues queries on demand. This makes selectorless web extraction a primitive for autonomous research, comparison, and monitoring agents.

Given a startup's homepage, query for product page links, follow each, and extract pricing into a single comparison object

Key Endpoints

3 endpoints — jentic publishes the only available openapi specification for agentql api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/query-data

Query data from a web page

POST

/query-document

Query data from a PDF or image

POST

/tetra/sessions

Create a remote browser session

POST

/query-data

Query data from a web page

POST

/query-document

Query data from a PDF or image

POST

/tetra/sessions

Create a remote browser session

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential management

Credential isolation

AgentQL API keys live in the Jentic vault and are injected as X-API-Key at execution time. Agents never see the raw key in their context.

Intent-based discovery

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, including the supported query syntax.

Time to first call

Time to first call

Direct AgentQL integration: 1-2 hours for auth, query construction, and Tetra lifecycle. Through Jentic: under 10 minutes — search, load, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Browserless

→

Headless Chrome with raw HTML, screenshots, and PDF output

Choose Browserless when the agent needs raw page artifacts rather than parsed fields, or when it has its own extraction logic.

Alternative

Apify API

→

Pre-built site-specific scrapers (Actors) with persistent dataset storage

Choose Apify for major sites with maintained Actors (Amazon, Google, Twitter) and when persistent dataset output is needed.

Complementary

ZenRows

→

Proxy and anti-bot bypass for hard-to-fetch targets

Use ZenRows to fetch a blocked target page first, then pass the rendered HTML to AgentQL for structured extraction.

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 value never reaches the agent's context.

Can I scrape sites that require login with AgentQL?

Yes, by using Tetra. POST /tetra/sessions to create a session, drive it through the login flow, then run /query-data calls scoped to that session id. Static page queries against /query-data alone do not handle authentication.

What are the rate limits for the AgentQL API?

Limits are enforced as monthly query and Tetra-minute quotas tied to your plan rather than a hard requests-per-second cap. Build retry-with-backoff into the agent for 429 responses.

How do I extract structured data from a URL through Jentic?

Run the Jentic search 'extract structured data from a web page'. Jentic returns the POST /query-data operation; load its schema, supply the url and an AgentQL query like '{ products[] { name price } }', and execute. The parsed object comes back in the response.

Does AgentQL accept natural language instead of AgentQL syntax?

Yes. Both /query-data and /query-document accept a prompt parameter. The shape of the returned JSON is inferred from the prompt rather than declared explicitly in a query.

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View OpenAPI Document