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224 changes: 224 additions & 0 deletions sources/platform/integrations/ai/agent-onboarding.md
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---
title: Agent onboarding
sidebar_label: Agent onboarding
description: Connect your AI agent to Apify. Set up the MCP server, install Agent Skills + CLI, or integrate via the API client.
sidebar_position: 0
slug: platform/integrations/agent-onboarding
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Slug format causes incorrect URL path resolution

High Severity

The slug value platform/integrations/agent-onboarding is missing a leading / and incorrectly includes the platform/ prefix. Every other doc in this directory uses an absolute slug pattern like /integrations/crewai. Since the Docusaurus docs plugin already sets routeBasePath: 'platform', this relative slug gets resolved against the file's directory, producing a deeply nested and incorrect URL instead of the intended /platform/integrations/agent-onboarding. The correct slug is /integrations/agent-onboarding.

Fix in Cursor Fix in Web

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Bugbot Autofix determined this is a false positive.

The file mentioned in the bug report (agent-onboarding.md with slug 'platform/integrations/agent-onboarding') does not exist; the actual file is ai-agents.md with correct slug '/integrations/ai-agents', and git history shows all versions always had correct slug format with leading slash.

This Bugbot Autofix run was free. To enable autofix for future PRs, go to the Cursor dashboard.

toc_max_heading_level: 3
---

import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';

Connect your AI agent or application to Apify - the platform for web scraping, data extraction, and browser automation. The typical agent workflow: find an Actor, run it, get structured data back.

This page explains how to integrate AI agents with the Apify platform, based on your use case. It covers how to connect, run Actors, retrieve data, and access documentation programmatically.

**Core concepts:**

- **Actors** - Serverless cloud programs that perform scraping, crawling, or automation tasks. Thousands of ready-made Actors are available in [Apify Store](https://apify.com/store).

Check failure on line 19 in sources/platform/integrations/ai/agent-onboarding.md

View workflow job for this annotation

GitHub Actions / lint

[vale] reported by reviewdog 🐶 [Vale.Terms] Use 'serverless' instead of 'Serverless'. Raw Output: {"message": "[Vale.Terms] Use 'serverless' instead of 'Serverless'.", "location": {"path": "sources/platform/integrations/ai/agent-onboarding.md", "range": {"start": {"line": 19, "column": 16}}}, "severity": "ERROR"}
- **Datasets** - Append-only storage for structured results. Every Actor run creates a default dataset. Export as JSON, CSV, Excel, XML, or RSS.
- **API** - RESTful API at `https://api.apify.com/v2` for all platform operations. Also accessible via [MCP](./mcp.md), [CLI](/cli), and client libraries.

## Prerequisites

Sign up at [console.apify.com](https://console.apify.com/sign-up) using Google or GitHub. The free plan includes monthly platform usage credits with no credit card required. Get your API token from **[Console > Settings > Integrations](https://console.apify.com/settings/integrations)**.

:::tip Free exploration
The MCP server's `search-actors`, `fetch-actor-details`, and docs tools work **without authentication**. You can browse Actors and documentation without an account.
:::

## Choose your integration method

| Method | Best for | Auth |
|--------|----------|------|
| [MCP server](#mcp-server) | AI agents and coding assistants | OAuth or API token |
| [Agent Skills](#agent-skills) | Guided scraping workflows and Actor development | API token |
| [API client](#api-client) | Backend apps (JavaScript/Python) | API token |
| [CLI](#cli) | Building and deploying custom Actors | API token |
| [REST API](#rest-api) | Any language, HTTP integrations, no-code tools | API token |

### MCP server

The [Apify MCP server](./mcp.md) connects your agent to the full Apify platform via the [Model Context Protocol](https://modelcontextprotocol.io/). No local installation needed for remote-capable clients.

**Remote (recommended)** - works with Claude Code, Cursor, VS Code, GitHub Copilot, and other remote-capable clients:

```json
{
"mcpServers": {
"apify": {
"url": "https://mcp.apify.com"
}
}
}
```

OAuth handles authentication automatically - you'll be prompted to sign in on first use.

**Local/stdio** - for clients that only support local MCP servers (e.g. Claude Desktop):

```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": ["-y", "@apify/actors-mcp-server"],
"env": { "APIFY_TOKEN": "YOUR_TOKEN" }
}
}
}
```

For client-specific setup instructions, use the [MCP Configurator](https://mcp.apify.com) which generates ready-to-paste configs. For advanced options and tool customization, see the full [MCP server documentation](./mcp.md).

### Agent Skills

Pre-built workflows that guide AI agents through data extraction and Actor development tasks.

```bash
npx skills add apify/agent-skills
```

| Skill | What it does |
|-------|-------------|
| `apify-ultimate-scraper` | Routes web scraping requests to the right Actor for multi-step data pipelines |
| `apify-actor-development` | Guided workflow for building and deploying custom Actors |
| `apify-actorization` | Converts an existing project into an Apify Actor |
| `apify-generate-output-schema` | Auto-generates output schemas from Actor source code |

Skills work with Claude Code, Cursor, Gemini CLI, and OpenAI Codex. See the [skills registry](https://skills.sh/apify/agent-skills) for and details.

### API client

For integrating Apify into your application code.

:::warning Package naming
`apify-client` is the API client for **calling** Actors. The `apify` package is the SDK for **building** Actors. For backend integration, install `apify-client`.
:::

<Tabs>
<TabItem value="javascript" label="JavaScript / TypeScript">

```bash
npm install apify-client
```

```typescript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('apify/web-scraper').call({
startUrls: [{ url: 'https://example.com' }],
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
```

Full reference: [JavaScript API client docs](https://docs.apify.com/api/client/js)

</TabItem>
<TabItem value="python" label="Python">

```bash
pip install apify-client
```

```python
import os
from apify_client import ApifyClient

client = ApifyClient(token=os.environ['APIFY_TOKEN'])
run = client.actor('apify/web-scraper').call(
run_input={'startUrls': [{'url': 'https://example.com'}]}
)
items = client.dataset(run['defaultDatasetId']).list_items().items
```

Full reference: [Python API client docs](https://docs.apify.com/api/client/python)

</TabItem>
</Tabs>

### CLI

For running Actors and building custom ones from the command line.

```bash
npm install -g apify-cli # or: brew install apify-cli
apify login # authenticate with your API token

# Discover Actors
apify actors info apify/web-scraper --readme # get Actor README
apify actors info apify/web-scraper --input # get input schema

# Run an Actor and get output
apify actors call apify/web-scraper \
-i '{"startUrls": [{"url": "https://example.com"}]}' \
--output-dataset

# Build and deploy custom Actors
apify create my-actor # scaffold (JS/TS/Python)
apify run # test locally
apify push # deploy to Apify cloud
```

Full reference: [Apify CLI documentation](/cli)

### REST API

For HTTP-native integrations or languages without a dedicated client. Base URL: `https://api.apify.com/v2`. Authenticate with `Authorization: Bearer YOUR_TOKEN` header.

**Quick reference:**

| Action | Method | Endpoint |
|--------|--------|----------|
| Search Actors in Store | `GET` | `/v2/store` |
| Get Actor details | `GET` | `/v2/acts/{actorId}` |
| Run an Actor | `POST` | `/v2/acts/{actorId}/runs` |
| Run Actor (sync, get results) | `POST` | `/v2/acts/{actorId}/run-sync-get-dataset-items` |
| Get run status | `GET` | `/v2/actor-runs/{runId}` |
| Get dataset items | `GET` | `/v2/datasets/{datasetId}/items` |

The sync endpoint (`run-sync-get-dataset-items`) runs an Actor and returns results in a single request (waits up to 5 minutes). Use async endpoints for longer runs.

Full reference: [Apify API v2](/api/v2)

## Documentation access for agents

| Resource | How to access |
|----------|---------------|
| Specific doc page | Append `.md` to any docs URL (e.g. `docs.apify.com/platform/actors.md`) |
| Specific doc page (alt) | Request with `Accept: text/markdown` header |
| Docs index | [docs.apify.com/llms.txt](https://docs.apify.com/llms.txt) |
| Full docs (large) | [docs.apify.com/llms-full.txt](https://docs.apify.com/llms-full.txt) |
| Actor Store pages | Append `.md` to any Apify Store URL |
| MCP docs tools | `search-apify-docs`, `fetch-apify-docs` |

For targeted lookups, prefer `.md` URLs for specific pages or MCP docs tools over the full `llms-full.txt` file, which may be truncated by agents with limited context windows.

## Frequently asked questions

**Which package: `apify` or `apify-client`?**
`apify-client` is for **calling** Actors from your app. `apify` is the SDK for **building** Actors on the Apify platform. These are different packages.

**Can I use Apify without an account?**
Partially. The MCP server lets you search Actors, read details, and browse docs without authentication. Running Actors requires a free account.

**How do I find the right Actor?**
Use `search-actors` via MCP, browse [Apify Store](https://apify.com/store), or ask your AI agent. Every Actor has a README with capabilities and input schema.

**What's the difference between MCP and Agent Skills?**
MCP connects your agent to Apify as a tool provider (search, run, get results). Agent Skills add guided workflows on top - multi-step scraping across platforms, Actor development lifecycle, and more.

**Can I build my own Actor?**
Yes. Install the [CLI](/cli), run `apify create`, and follow the prompts. Use the `apify-actor-development` skill for a guided workflow. Deploy with `apify push`.

## Useful resources

- **[MCP server integration](./mcp.md)** - Tool customization, dynamic Actor discovery, and advanced config
- **[CLI documentation](/cli)** - Complete command reference
- **[API reference](/api/v2)** - All REST API endpoints
- **[API client for JavaScript](https://docs.apify.com/api/client/js)** | **[for Python](https://docs.apify.com/api/client/python)** - Client libraries
- **[Storage documentation](/platform/storage)** - Datasets, key-value stores, and request queues
- **[Build with AI](/platform/actors/development)** - Build and deploy your first Actor
- **[Framework integrations](./crewai.md)** - CrewAI, LangChain, LlamaIndex, and more
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