# Zendesk Help Center Scraper (`bindler/zendesk-help-center-scraper`) Actor

Scrape all articles from any Zendesk Help Center. Full plain-text bodies with sections, categories and labels. Ready for RAG, AI support bots and knowledge base migration.

- **URL**: https://apify.com/bindler/zendesk-help-center-scraper.md
- **Developed by:** [Neil Sangwaiya](https://apify.com/bindler) (community)
- **Categories:** AI, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Zendesk Help Center Scraper

Extract every article from **any Zendesk Help Center** as clean plain text, with sections, categories, labels and vote counts. Built for RAG pipelines, AI support agents, knowledge base migration and competitive research.

Thousands of companies run their documentation on Zendesk Guide: Discord, Figma, Zendesk itself, and countless others. Every one of them exposes a public API. Paste the help centre URL and go. No API key, no login, no configuration.

### What you get

| Field | Description |
|---|---|
| `id` | Zendesk article ID |
| `title` | Article title |
| `url` | Public article link |
| `body` | **Full article as clean plain text** |
| `wordCount` | Words in the body |
| `section` / `sectionId` | Section name, not just an ID |
| `category` / `categoryId` | Category name, not just an ID |
| `labels` | Article labels |
| `locale` | Article language |
| `createdAt` / `updatedAt` / `editedAt` | Timestamps |
| `voteSum` / `voteCount` | Reader feedback |
| `promoted` / `outdated` | Zendesk article flags |
| `helpCenter` | Source help centre |
| `scrapedAt` | ISO timestamp |

### Why this one

**Locale is detected for you.** Zendesk redirects `/api/v2/help_center/articles.json` to a locale-specific path, and scrapers that ignore this get a redirect instead of data. This Actor resolves the locale on the first call and then goes direct.

**Category and section names, not IDs.** Zendesk returns `section_id: 4402024389911`, which is useless on its own. This Actor fetches the full taxonomy first and attaches real names, so your records are readable and filterable without a second pass.

**Plain text, not HTML.** Article bodies come back as HTML full of markup. Feeding that to a model wastes tokens. This strips it properly, including entity decoding, so records drop straight into a vector store.

**Honest rate limiting.** Zendesk returns `Retry-After` on 429 and this Actor respects it rather than hammering and failing.

### Use it for

- Building a RAG corpus from your own or a competitor's documentation
- Feeding an AI support agent with accurate product knowledge
- Migrating a knowledge base off Zendesk
- Auditing which articles are outdated or poorly rated

### Example input

```json
{
  "helpCenterUrl": "https://support.discord.com",
  "maxArticles": 500,
  "includeBody": true
}
```

### Filters

- **Locale** — leave blank to auto-detect, or force one such as `de`, `fr`, `ja`
- **Category ID** or **Section ID** — restrict to one part of the help centre
- **Max articles** — caps the run so cost is predictable
- **Include full text** — turn off for a fast title-and-URL index

### Notes

- Uses only the public, unauthenticated Zendesk Help Center API. No login, no agent-side data, no tickets.
- Works on any Zendesk Guide instance, including custom domains.

# Actor input Schema

## `helpCenterUrl` (type: `string`):

Any Zendesk Help Center, e.g. https://support.discord.com or https://help.figma.com

## `locale` (type: `string`):

Optional. Leave blank to detect automatically. Examples: en-us, de, fr, ja.

## `categoryId` (type: `string`):

Optional. Restrict to one category.

## `sectionId` (type: `string`):

Optional. Restrict to one section. Takes priority over category.

## `maxArticles` (type: `integer`):

Stop after this many. Controls your cost.

## `includeBody` (type: `boolean`):

Turn off for a fast index of titles and URLs only.

## Actor input object example

```json
{
  "helpCenterUrl": "https://support.discord.com",
  "maxArticles": 200,
  "includeBody": true
}
```

# Actor output Schema

## `articles` (type: `string`):

One record per article with full plain-text body, section and category names, labels and vote counts.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

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

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "helpCenterUrl": "https://support.discord.com"
};

// Run the Actor and wait for it to finish
const run = await client.actor("bindler/zendesk-help-center-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "helpCenterUrl": "https://support.discord.com" }

# Run the Actor and wait for it to finish
run = client.actor("bindler/zendesk-help-center-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "helpCenterUrl": "https://support.discord.com"
}' |
apify call bindler/zendesk-help-center-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bindler/zendesk-help-center-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/pYn8jXiGZ36Hce4Xc/builds/GazMnlF8Qmfnqpv9N/openapi.json