McMaster-Carr Product Scraper

Extract public McMaster-Carr catalog intelligence from category, search, and product-family pages. This actor captures product-family metadata, visible specification filters, category links, source URLs, and scrape timestamps from the dynamic McMaster-Carr catalog.

What does McMaster-Carr Product Scraper do?

McMaster-Carr Product Scraper opens McMaster-Carr catalog pages in a browser and listens for the first-party catalog data that powers the page.

It can collect:

• Product-family names
• Product counts
• Presentation counts
• Catalog category links
• Visible specification filters
• Filter values and product counts
• Source URLs
• Login-wall detection
• Scrape timestamps

Who is it for?

This scraper is designed for industrial and MRO workflows.

• Procurement teams comparing catalog coverage
• Ecommerce analysts monitoring industrial supply categories
• Engineering sourcing teams mapping part families
• Catalog data teams building product taxonomies
• Price and assortment intelligence teams
• Operations teams researching replacement parts

Why use this actor?

McMaster-Carr is a large dynamic catalog. Manual catalog review is slow when you need to compare many product families or understand category structure.

This actor turns public catalog pages into structured dataset rows that are easy to export, filter, and enrich.

What data can you extract?

Field	Description
entityType	product_family, spec_filter, or catalog_category
title	Human-readable record title
productFamily	McMaster product-family name when available
productCount	Public product count when exposed
presentationCount	Presentation count when exposed
attributeName	Specification/filter name
attributeValues	Visible values with counts and links
requestedUrl	URL or keyword-derived URL requested by the actor
sourceUrl	Final source URL for the row
loginWallDetected	Whether McMaster displayed a login wall during browsing
scrapeTimestamp	ISO timestamp for the scrape

How much does it cost to scrape McMaster-Carr products?

The actor uses pay-per-event pricing.

• A start event is charged once per run: $0.005.
• Each saved dataset item is charged with tiered pricing.
• Tier discounts apply automatically based on your Apify plan.

Apify plan tier	Price per saved item
FREE	$0.00020828
BRONZE	$0.00018111
SILVER	$0.00014127
GOLD	$0.00010867
PLATINUM	$0.000072445
DIAMOND	$0.000050711

Cost examples:

Calculated as the $0.005 start event + saved items × the applicable item rate.

Run size	FREE plan estimate	BRONZE plan estimate	What it covers
25 items	about $0.0103	about $0.0095	Quick category test
50 items	about $0.0154	about $0.0141	Typical validation run
500 items	about $0.1091	about $0.0956	Larger catalog-mapping batch

Free-plan example: a 50-item run costs about $0.0154 in actor charges ($0.005 start + 50 × $0.00020828). Use a low maxItems value for first tests, then increase once the output matches your workflow.

Quick start

1. Open the actor on Apify.
2. Add one or more McMaster-Carr category or search URLs.
3. Optionally add keywords such as socket head screws or bearings.
4. Set maxItems.
5. Run the actor.
6. Export results from the dataset as JSON, CSV, Excel, or via API.

Input options

Category or search URLs

Use McMaster URLs such as:

https://www.mcmaster.com/products/screws/
https://www.mcmaster.com/products/bearings/

Keywords

Keywords are converted into McMaster URL slugs.

Example:

{
  "keywords": ["socket head screws", "bearings"]
}

Maximum records

maxItems controls the maximum number of rows saved.

Start small for testing:

{
  "maxItems": 25
}

Include spec filters

Set includeDetails to true to collect visible public specification filters and values.

{
  "includeDetails": true
}

Example input

{
  "startUrls": [
    { "url": "https://www.mcmaster.com/products/screws/" }
  ],
  "keywords": ["bearings"],
  "maxItems": 50,
  "includeDetails": true,
  "proxyConfiguration": { "useApifyProxy": false }
}

Example output

{
  "entityType": "product_family",
  "requestedUrl": "https://www.mcmaster.com/products/screws/",
  "sourceUrl": "https://www.mcmaster.com/products/screws/",
  "title": "Socket Head Screws",
  "productFamily": "Socket Head Screws",
  "productCount": 7979,
  "presentationCount": 39,
  "pageType": "product_family_landing_page",
  "loginWallDetected": true,
  "scrapeTimestamp": "2026-07-09T04:41:49.387Z"
}

Working with login-wall detection

McMaster-Carr may show a message such as To continue browsing, please log in after initial public catalog hydration.

The actor does not collect private account data and does not require McMaster credentials.

When this happens, loginWallDetected is set to true so downstream workflows can separate public metadata from pages that were not fully browsable.

Tips for reliable runs

• Use category URLs for the most stable results.
• Keep maxItems low while testing.
• Use includeDetails: false if you only need category discovery.
• Avoid very large keyword batches in one run.
• Use datacenter proxy first if a proxy is needed.
• Use residential proxy only if datacenter is blocked.

Integrations

You can connect the dataset to concrete industrial workflows:

• Procurement dashboards: refresh screw, bearing, fastener, or raw-material category coverage each week and chart product-family counts.
• Google Sheets: export CSV rows for sourcing analysts who need a quick sortable catalog map without writing code.
• Airtable: maintain a lightweight product-family tracker with owner, sourcing status, and notes per category.
• Snowflake or BigQuery: append scheduled runs into a warehouse table and compare category/filter changes over time.
• Internal PIM systems: seed taxonomy enrichment queues with public McMaster product-family names and spec attributes.
• Price-monitoring jobs: use category and filter rows to identify which product families should be checked manually or by an account-authorized internal process.
• Catalog taxonomy enrichment: merge McMaster public attribute names with your internal MRO vocabulary for search and faceted navigation.

API usage with Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/mcmaster-carr-product-scraper').call({
  startUrls: [{ url: 'https://www.mcmaster.com/products/screws/' }],
  maxItems: 25,
  includeDetails: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

API usage with Python

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('automation-lab/mcmaster-carr-product-scraper').call(run_input={
    'startUrls': [{'url': 'https://www.mcmaster.com/products/screws/'}],
    'maxItems': 25,
    'includeDetails': True,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

API usage with cURL

curl -X POST "https://api.apify.com/v2/acts/automation-lab~mcmaster-carr-product-scraper/runs?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"startUrls":[{"url":"https://www.mcmaster.com/products/screws/"}],"maxItems":25,"includeDetails":true}'

Use with MCP

Connect this actor to AI tools through Apify MCP.

MCP URL:

https://mcp.apify.com/?tools=automation-lab/mcmaster-carr-product-scraper

Claude Code setup command:

claude mcp add apify-mcmaster-carr \
  --transport http \
  "https://mcp.apify.com/?tools=automation-lab/mcmaster-carr-product-scraper"

Claude Desktop, Cursor, or VS Code MCP JSON configuration:

{
  "mcpServers": {
    "apify-mcmaster-carr": {
      "url": "https://mcp.apify.com/?tools=automation-lab/mcmaster-carr-product-scraper",
      "headers": {
        "Authorization": "Bearer ${APIFY_TOKEN}"
      }
    }
  }
}

If your MCP client does not expand ${APIFY_TOKEN}, paste your Apify API token into the Authorization header locally. Keep the token private and do not commit it to a repository.

Example prompts:

• "Scrape public McMaster-Carr screw category metadata and summarize the main product families."
• "Extract spec filters for bearings from McMaster-Carr and group them by attribute."
• "Compare category counts across several McMaster-Carr product URLs."

Data quality notes

The actor extracts public catalog metadata exposed during page hydration. Some part-level pricing, inventory, CAD downloads, or account-specific data may require a logged-in McMaster session and is not collected.

Legality

This actor extracts publicly accessible catalog metadata. Make sure your use complies with McMaster-Carr terms, applicable laws, and your internal data governance rules.

FAQ

Why do I see loginWallDetected: true?

McMaster-Carr sometimes displays a login wall after the public page data loads. The actor records this flag instead of pretending that the page was fully available.

Why did I get category rows instead of product-family rows?

Some McMaster pages expose only browse-category links before showing a login wall. Try a more specific product URL or keyword.

Why are part numbers missing?

Part-level tables are not always exposed to anonymous public sessions. The actor saves product-family and filter metadata when part numbers are not available.

Related scrapers

Related automation-lab actors that can support catalog intelligence workflows:

• https://apify.com/automation-lab/uline-scraper
• https://apify.com/automation-lab/toolstation-scraper
• https://apify.com/automation-lab/costco-business-center-scraper

Changelog

0.1

Initial private build for McMaster-Carr public catalog metadata extraction.

Support

If a McMaster-Carr URL produces fewer records than expected, include the run ID, input JSON, and the target URL in your support request.

Limitations

• No private McMaster account login.
• No bypassing credential walls.
• Part-level price and stock may not be available anonymously.
• Dynamic catalog data can vary by page and session.

Best practices

• Use specific product-family URLs.
• Combine URLs and keywords for broader coverage.
• Store run inputs with your reports for reproducibility.
• Monitor loginWallDetected in downstream pipelines.
• Keep first test runs small.

Output formats

Apify datasets can be exported as:

• JSON
• JSONL
• CSV
• Excel
• XML
• RSS

Procurement workflow example

1. Scrape screw and bearing category URLs.
2. Export product-family rows to CSV.
3. Group by productFamily and productCount.
4. Review spec filters for key attributes.
5. Feed selected families into internal sourcing research.

Catalog intelligence workflow example

1. Run keywords for a list of industrial part families.
2. Store the dataset in BigQuery.
3. Track product counts over time.
4. Alert if a product family appears, disappears, or changes count significantly.

Final notes

McMaster-Carr Product Scraper is built for stable public catalog discovery. It is intentionally conservative around account-only data and records login-wall signals clearly for transparent downstream analysis.