apify · TC-MO · May 14, 2026 · May 13, 2026 · May 13, 2026 · May 13, 2026
diff --git a/.github/styles/config/vocabularies/Docs/accept.txt b/.github/styles/config/vocabularies/Docs/accept.txt
@@ -7,7 +7,7 @@ CU
 booleans
 env
 npm
-serverless
+[Ss]erverless
 [Bb]oolean
 node_modules
 [Rr]egex

diff --git a/sources/platform/actors/development/quick-start/build_with_ai.md b/sources/platform/actors/development/quick-start/build_with_ai.md
@@ -14,9 +14,10 @@ import TabItem from '@theme/TabItem';
 
 This guide provides best practices for building new Actors or improving existing ones using AI code generation tools by providing the AI agents with the right instructions and context.
 
-:::tip Develop AI agents on Apify
+:::tip Different goal?
 
-Looking to build and deploy AI agents as Actors? See [Develop AI agents on Apify](/platform/actors/development/quick-start/develop-ai-agents) for the full stack - templates, sandboxes, LLM access, and monetization.
+- _Building and deploying AI agents as Actors on Apify?_ See [Develop AI agents on Apify](/platform/actors/development/quick-start/develop-ai-agents) for the full stack - templates, sandboxes, LLM access, and monetization.
+- _Connecting an external AI agent to Apify?_ See [Apify for AI agents](/platform/integrations/agent-onboarding) for MCP, Agent Skills, client libraries, and the REST API.
 
 :::
 

diff --git a/sources/platform/index.mdx b/sources/platform/index.mdx
@@ -33,6 +33,11 @@ Learn how to run any Actor in Apify Store or create your own. A step-by-step gui
         desc="Learn everything about web scraping and automation with free courses that will turn you into an expert scraper developer."
         to="/academy"
     />
+    <Card
+        title="Apify for AI agents"
+        desc="Connect your AI agent to the Apify platform to scrape the web, run Actors, and retrieve structured data."
+        to="/platform/integrations/agent-onboarding"
+    />
 </CardGrid>
 
 ## Contents

@@ -0,0 +1,306 @@
+---
+title: Apify for AI agents
+sidebar_label: Agent onboarding
+description: Connect your AI agent to the Apify platform - scrape the web, run Actors, and retrieve structured data via MCP, Agent Skills, client libraries, or the REST API.
+sidebar_position: 1
+slug: /integrations/agent-onboarding
+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.
+
+## 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).
+- _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](/platform/integrations/mcp), [CLI](/cli), and client libraries.
+
+## Prerequisites
+
+Sign up to [Apify Console](https://console.apify.com/sign-up). 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.
+
+:::
+
+## Run your first Actor
+
+Every Apify Actor follows the same pattern: send input as JSON, get structured data back. The shortest path through each of the main integration methods, using the agent-optimized [RAG Web Browser](https://apify.com/apify/rag-web-browser) Actor:
+
+<Tabs>
+<TabItem value="mcp" label="MCP">
+
+After [connecting the MCP server](#mcp-server) to your AI assistant, ask:
+
+```text
+Use Apify's RAG Web Browser to find the top 3 pages about Apify documentation, then summarize.
+```
+
+Your agent calls [`search-actors`](/platform/integrations/mcp#available-tools), [`call-actor`](/platform/integrations/mcp#available-tools), and reads the resulting dataset items - all through MCP, no code required.
+
+</TabItem>
+<TabItem value="javascript" label="JavaScript">
+
+```typescript
+import { ApifyClient } from 'apify-client';
+
+const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
+const run = await client.actor('apify/rag-web-browser').call({
+    query: 'Apify documentation',
+    maxResults: 3,
+});
+const { items } = await client.dataset(run.defaultDatasetId).listItems();
+```
+
+</TabItem>
+<TabItem value="python" label="Python">
+
+```python
+import os
+from apify_client import ApifyClient
+
+client = ApifyClient(token=os.environ['APIFY_TOKEN'])
+run = client.actor('apify/rag-web-browser').call(
+    run_input={'query': 'Apify documentation', 'maxResults': 3},
+)
+items = client.dataset(run['defaultDatasetId']).list_items().items
+```
+
+</TabItem>
+<TabItem value="cli" label="CLI">
+
+```bash
+apify login                                       # one-time
+apify call apify/rag-web-browser \
+    -i '{"query": "Apify documentation", "maxResults": 3}' \
+    --output-dataset
+```
+
+</TabItem>
+</Tabs>
+
+The pattern is the same across every integration method: pick an Actor, send input, receive structured data. Choose the connection method below that fits your stack.
+
+:::caution Cost controls
+
+When an agent calls Actors automatically, set run limits to prevent surprise bills. Pass these as query parameters on the [run Actor endpoint](/api/v2/act-runs-post):
+
+- `memory` (MB) - power of 2, minimum 128. Lower memory means lower cost per second.
+- `timeout` (seconds) - cap how long a single run can last.
+- `maxTotalChargeUsd` - cap total run cost for pay-per-event Actors.
+
+See [Usage and resources](/platform/actors/running/usage-and-resources) and [Billing](/platform/console/billing) for details.
+
+:::
+
+## Choose your integration method
+
+| Method | Best for | Auth |
+| :--- | :--- | :--- |
+| [MCP server](#mcp-server) | AI agents and coding assistants | OAuth or 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](/platform/integrations/mcp) 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.
+
+1. Add the following to your MCP client's configuration:
+
+    ```json
+    {
+      "mcpServers": {
+        "apify": {
+          "url": "https://mcp.apify.com"
+        }
+      }
+    }
+    ```
+
+1. Restart your client and sign in when prompted. OAuth handles authentication automatically.
+
+#### Local/stdio
+
+For clients that only support local MCP servers, for example Claude Desktop.
+
+1. Add the following to your MCP client's configuration:
+
+    ```json
+    {
+      "mcpServers": {
+        "apify": {
+          "command": "npx",
+          "args": ["-y", "@apify/actors-mcp-server"],
+          "env": { "APIFY_TOKEN": "YOUR_TOKEN" }
+        }
+      }
+    }
+    ```
+
+1. Replace `YOUR_TOKEN` with your API token and restart the client.
+
+For client-specific setup instructions, use the [MCP Configurator](https://mcp.apify.com) which generates ready-to-paste configs. For details, see the [MCP server documentation](/platform/integrations/mcp).
+
+### 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.
+
+Install on macOS or Linux (Windows and Homebrew alternatives in the [CLI install docs](/cli/docs/installation)):
+
+```bash
+curl -fsSL https://apify.com/install-cli.sh | bash
+apify login                                      # authenticate with your API token
+```
+
+Discover and inspect Actors:
+
+```bash
+apify actors search scraping                     # search Apify Store
+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 its output:
+
+```bash
+apify actors call apify/web-scraper \
+    -i '{"startUrls": [{"url": "https://example.com"}]}' \
+    --output-dataset
+```
+
+Build and deploy custom Actors:
+
+```bash
+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 the `Authorization: Bearer YOUR_TOKEN` header.
+
+#### Quick reference
+
+| Action | Method | Endpoint |
+| :--- | :--- | :--- |
+| [Search Actors in Store](/api/v2/store-get) | `GET` | `/v2/store` |
+| [Get Actor details](/api/v2/act-get) | `GET` | `/v2/acts/{actorId}` |
+| [Run an Actor](/api/v2/act-runs-post) | `POST` | `/v2/acts/{actorId}/runs` |
+| [Run Actor (sync, get results)](/api/v2/act-run-sync-get-dataset-items-post) | `POST` | `/v2/acts/{actorId}/run-sync-get-dataset-items` |
+| [Get run status](/api/v2/actor-run-get) | `GET` | `/v2/actor-runs/{runId}` |
+| [Get dataset items](/api/v2/dataset-items-get) | `GET` | `/v2/datasets/{datasetId}/items` |
+
+The sync endpoint ([`run-sync-get-dataset-items`](/api/v2/act-run-sync-get-dataset-items-post)) runs an Actor and returns results in a single request (waits up to 5 minutes). Use [async endpoints](/api/v2/act-runs-post) for longer runs.
+
+For runs that take longer than the sync timeout, prefer [webhooks](/platform/integrations/webhooks) over polling - Apify will POST a notification to your URL when the run finishes, avoiding wasted requests.
+
+Full reference: [Apify API v2](/api/v2).
+
+## Agent Skills
+
+Once you connect an agent via MCP or a coding assistant, [Apify Agent Skills](https://skills.sh/apify/agent-skills) add pre-built workflows on top - guiding the agent through multi-step scraping pipelines and Actor development tasks. Skills are not a separate integration method; they layer over your existing connection.
+
+Install into Claude Code, Cursor, Gemini CLI, or OpenAI Codex:
+
+```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 |
+
+For the full list and details, see the [skills registry](https://skills.sh/apify/agent-skills).
+
+## Documentation access for agents
+
+Apify documentation is available in formats optimized for programmatic consumption.
+
+| Resource | How to access |
+| :--- | :--- |
+| Specific doc page | Append `.md` to any docs URL (for example, `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 the MCP docs tools over the full `llms-full.txt` file. Agents with limited context windows may not load `llms-full.txt` fully.
+
+## Useful resources
+
+- [MCP server integration](/platform/integrations/mcp) - Tool customization, dynamic Actor discovery, and advanced configuration
+- [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
@@ -2,7 +2,7 @@
 title: Apify MCP server
 sidebar_label: MCP server
 description: Learn how to use the Apify MCP server to integrate Apify's library of Actors into your AI agents or large language model-based applications.
-sidebar_position: 1
+sidebar_position: 0
 slug: /integrations/mcp
 toc_max_heading_level: 4
 ---

@@ -171,9 +171,15 @@ The Apify platform integrates with popular ETL and data pipeline services, enabl
 <br />
 
 If you are working on AI/LLM-related applications, we recommend looking into the many integrations with popular AI/LLM ecosystems.
-These integrations allow you to use Apify Actors as tools and data sources.
+These integrations allow you to use Apify Actors as tools and data sources. If you are connecting any AI agent to Apify, start with the [Apify for AI agents](/platform/integrations/agent-onboarding) page.
 
 <CardGrid>
+    <Card
+        title="AI agents"
+        desc="Connect your AI agent to Apify using MCP, Agent Skills, client libraries, or the REST API."
+        to="/platform/integrations/agent-onboarding"
+        smallImage
+    />
     <Card
         title="CrewAI"
         to="./integrations/crewai"