Coursera Course & Specialization Catalog Scraper: MCP config, n8n workflow and API

{
  "mode": "search",
  "query": "machine learning",
  "productTypes": [
    "COURSE"
  ],
  "freeOnly": false,
  "sortBy": "BEST_MATCH",
  "maxItems": 3,
  "includeDetails": false
}

---
name: coursera-course-and-specialization-catalog-scraper
description: "Coursera courses, specializations and credential products with ratings, skills, partners, level, duration, languages, access flags, and optional syllabus, instructors, enrollment, page views and top reviews. Runs the Apify Actor nimbryxo-studio/coursera-course-and-specialization-catalog-scraper. Use when the user needs Coursera Course data with fields such as recordType, name, partnerName, difficultyLevel, avgRating, learnerCount and an Apify token is available."
compatibility: "Needs network access, curl, and an APIFY_TOKEN environment variable. Runs are billed to the token owner's Apify account."
metadata:
  actor: "nimbryxo-studio/coursera-course-and-specialization-catalog-scraper"
  store-url: "https://apify.com/nimbryxo-studio/coursera-course-and-specialization-catalog-scraper"
---

# Coursera Course & Specialization Catalog Scraper

Use this skill to fetch Coursera Course data with the Apify Actor `nimbryxo-studio/coursera-course-and-specialization-catalog-scraper` and work with the returned rows.

## Before running

1. Check that `APIFY_TOKEN` is set in the environment. Never print it or write it to a file.
2. Build `input.json` from the user's request using the fields below. Keep limits small for a first run.
3. Confirm the search terms or URLs with the user if the request is ambiguous.

## Input fields

| Field | Type | Meaning |
| --- | --- | --- |
| `mode` | one of `search`, `byCategory`, `byPartner`, `bySlug`, `byUrl`, `byIds`, `browse`, `searchSpecializations`, required | What to fetch. `bySlug`, `byUrl` and `byIds` always return detail fields for the looked-up products. |
| `query` | string | Keyword search (mode=search, searchSpecializations). Optional narrowing keyword for byCategory and byPartner. |
| `startUrls` | array | Course, specialization, professional certificate, guided project, degree or certificate page, or a Coursera search / courses URL. Search URLs are converted into catalog filters. |
| `slugs` | array | Course or specialization slugs, e.g. `machine-learning`. A full Coursera URL is also accepted. |
| `productIds` | array | Coursera product IDs such as `course~8UjeMk-mEeit4g4GsxE4dg` or `s12n~nOOfCDWeEeuiZgo2K4rorQ`. Bare course IDs are also accepted. |
| `productTypes` | array | Limit results to these Coursera product types. Leave empty for every type. |
| `difficulties` | array | Only include products at these difficulty levels. |
| `durations` | array | Only include products in these duration bands. |
| `costs` | array | Only include products with these cost labels. |
| `topics` | array | Only include products in these subject areas (mode=byCategory requires at least one). |
| `languages` | array | Only include products available in these content languages. |
| `subtitleLanguages` | array | Only include products with subtitles in these languages. |
| `handsOnLearningTypes` | array | Only include products with these hands-on learning formats. |
| `tools` | array | Only include products that teach these tools or software skills. |

Example `input.json` (the Actor's published prefill):

```json
{
  "mode": "search",
  "query": "machine learning",
  "productTypes": [
    "COURSE"
  ],
  "freeOnly": false,
  "sortBy": "BEST_MATCH",
  "maxItems": 3,
  "includeDetails": false
}
```

## Run

```bash
curl -sS -X POST "https://api.apify.com/v2/acts/nimbryxo-studio~coursera-course-and-specialization-catalog-scraper/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d @input.json > results.json
```

The call waits for the run to finish and returns the dataset items as a JSON array. If the run needs more than 300 seconds the API answers with HTTP 408; then start the run with `POST /v2/acts/nimbryxo-studio~coursera-course-and-specialization-catalog-scraper/runs`, poll `GET /v2/actor-runs/{runId}` until `SUCCEEDED`, and read `GET /v2/datasets/{defaultDatasetId}/items`.

## Output

Each item is one record. Published fields include: `recordType`, `name`, `partnerName`, `difficultyLevel`, `avgRating`, `learnerCount`, `courseUrl`.

Summarise what was found, cite the record URLs when present, and say how many items came back. Do not invent values for empty fields.