Amcal AU Pharmacy Product Scraper

Extract Amcal Australia products, local prices, stock signals, categories, barcodes, descriptions, ingredients, directions, warnings, and pharmacy locations as structured datasets.

Use this Actor for pharmacy price monitoring, product enrichment, assortment research, local availability checks, health catalog analysis, and ecommerce automation.

This is an unofficial Actor and is not affiliated with Amcal. Product information is not medical advice; verify important information against the retailer and the product label.

What you can collect

• search — search the Amcal catalog with local price and stock context
• item — retrieve one exact rich product record
• categories — export the current category tree and filter metadata
• category — browse a leaf category with a bounded result limit
• locations — find pharmacy locations that can provide local catalog context
• search_filters — export supported sort modes and live categories

Product rows can include:

• identity: id, name, brand, barcode, slug, source_url
• commerce: price, discount_price, availability, in_stock
• package data: size, unit, unit_quantity
• catalog data: category, breadcrumbs, images
• rich item data: description, ingredients, active ingredient, directions, dosage, warnings, disclosure statements, and storage instructions

The default Dataset contains collected rows. The OUTPUT record in the default key-value store contains status, totals, errors, proxy diagnostics, and monetization metadata.

Quick start

Search products using a tested Amcal location:

{
  "operation": "search",
  "query": "panadol",
  "locationId": "15",
  "includeRaw": false
}

Retrieve one rich product record:

{
  "operation": "item",
  "itemId": "MMC-O100016239",
  "locationId": "15",
  "includeRaw": false
}

Browse a tested leaf category:

{
  "operation": "category",
  "categoryId": "3151",
  "categorySlug": "childrens-pain-relief",
  "locationId": "15",
  "page": 0,
  "limit": 10,
  "includeRaw": false
}

Find pharmacy locations:

{
  "operation": "locations",
  "postcode": "3195",
  "includeRaw": false
}

Operation guide

• search
  • required: query
  • optional: locationId, includeRaw
• item
  • required: itemId
  • optional: locationId, includeRaw
• categories
  • required: none
  • optional: includeRaw
• category
  • required: categoryId or categorySlug
  • optional: locationId, page, limit, sort, includeRaw
• locations
  • required: none
  • optional: postcode, includeRaw
• search_filters
  • required: none
  • optional: includeRaw

Use a leaf category for product browsing. Some top-level navigation categories are containers and correctly return no product rows.

Location-aware pricing

Amcal prices and stock can depend on the selected fulfilment pharmacy. Run locations first, then pass its id as locationId to search, category, or item.

The location service may include other pharmacies participating in the same fulfilment network. Location names are returned unchanged so you can decide which pharmacy context to use. Location 15 is the tested Amcal+ Pharmacy Mordialloc context.

Use with n8n / Make

A practical automation is:

Schedule -> run Actor -> wait for completion -> read Dataset -> Google Sheets / Telegram / CRM

An importable n8n starter is included in examples/n8n-amcal-search-to-google-sheets.json. Configure APIFY_TOKEN, Google Sheets credentials, and the destination spreadsheet before activation.

In Make:

1. Schedule the scenario.
2. Run Actor ZHl2neT8y6qqcWzon through the Apify API.
3. Wait for the run to finish.
4. Read defaultDatasetId.
5. Fetch clean Dataset items.
6. Route rows to Google Sheets, Telegram, or a CRM.

API run example:

curl -X POST \
  "https://api.apify.com/v2/acts/ZHl2neT8y6qqcWzon/runs?token=$APIFY_TOKEN&waitForFinish=120" \
  -H "Content-Type: application/json" \
  -d '{"operation":"search","query":"panadol","locationId":"15"}'

Then fetch the Dataset:

$curl "https://api.apify.com/v2/datasets/DATASET_ID/items?clean=true&format=json"

Keep API tokens in credentials or environment variables, never directly in a shared workflow.

Operational notes

• Direct HTTP is the cheapest verified route; no browser or paid proxy is required for the tested operations.
• page is zero-based.
• limit applies to category Dataset rows and accepts 1–100.
• Search currently returns the upstream bounded search page.
• includeRaw is intended for diagnostics and can make OUTPUT large.
• Empty source fields are removed from normalized output.