# Apify integrations: actors and actor runs

> Create an Actor, run a task and create a schedule in Apify, and start a workflow when Apify sends “Actor run created”.

**Canonical page:** https://tray.ai/connectors/apify-integrations/
**Categories:** Data and analytics
**Connects through:** HTTP Connector

## Overview

Apify is a web scraping and browser automation platform where you run ready-made or custom scrapers, called Actors, and store the data they collect. Tray.ai connects to Apify through the HTTP Connector, so your workflows can call the Apify API alongside the rest of your stack.

## Use cases

### Actors

Read and create actors in Apify from any Tray.ai workflow. The Apify API covers calls such as list Actors and create an Actor.

- List Actors
- Create an Actor
- Run an Actor

### Actor runs

Read actor runs in Apify from any Tray.ai workflow. The Apify API covers calls such as get a run and abort a run.

- Get a run
- Abort a run
- Get a run log

### Actor tasks

Read actor tasks in Apify from any Tray.ai workflow. The Apify API covers calls such as run a task and list task runs.

- Run a task
- List task runs

### Datasets

Read datasets in Apify from any Tray.ai workflow. The Apify API covers calls such as get dataset items and store dataset items.

- Get dataset items
- Store dataset items

### Key-value stores

Read and delete key-value stores in Apify from any Tray.ai workflow. The Apify API covers calls such as list keys and get a record.

- List keys
- Get a record
- Store a record

### Schedules

Create and update schedules in Apify from any Tray.ai workflow. The Apify API covers calls such as create a schedule and update a schedule.

- Create a schedule
- Update a schedule

## Challenges Tray.ai solves

### Keeping Apify credentials out of logs

A raw API call usually means pasting a key or token into the request, where it ends up in step inputs, logs, and screenshots.

**How Tray.ai helps:** Store Apify credentials once as a Tray.ai authentication and reference them from the HTTP Connector. Tray.ai masks authentication values in logs, so the secret never shows up in a step's input or output.

### Going from the Apify API docs to a working call

Translating an example request from API docs into a workflow step means copying the method, URL, headers, and body by hand.

**How Tray.ai helps:** Paste a cURL example from the Apify API docs into the HTTP Connector and Tray.ai fills in the method, URL, headers, and body for you.

### Handling files and non-JSON responses

Not every API answers in JSON. Some return XML, files, or binary data, or expect a multipart upload.

**How Tray.ai helps:** The HTTP Connector parses JSON and XML responses, returns files you can pass to the next step, and sends multipart form data for uploads.

## Frequently asked questions

### Does Tray.ai connect to Apify?

Yes. Tray.ai connects to Apify through the HTTP Connector, which calls the Apify API directly. Any call the Apify API documents can run as a step in a Tray.ai workflow.

### How does Tray.ai authenticate with Apify?

The Apify API uses a bearer token and an API key in the query string. You save it once as a Tray.ai authentication, and the HTTP Connector adds it to every request.

### Can I get a dedicated Apify connector?

Apify runs through the HTTP Connector rather than a dedicated connector. If your team wants one, the Tray.ai connector SDK can build a dedicated Apify connector from the Apify API.

## Learn more

- Intelligent Integration: https://tray.ai/platform/intelligent-ipaas/
- Merlin Agent Builder: https://tray.ai/platform/merlin-agent-builder/
- Agent Gateway for MCP: https://tray.ai/platform/agent-gateway/
- Book a demo: https://tray.ai/contact/