University Rankings Mega Pack Scraper

University Rankings Mega Pack Scraper

Scrape university rankings, institutional data, and online courses from Shanghai ARWU, THE Impact, US College Navigator, and Stanford Online in one run. Each university comes with its rank, scores, location, and course listings. Export to CSV, JSON, Excel, or XML.

Comparing universities across different ranking systems means visiting four different websites, running separate searches, and manually merging the results. This Actor queries Shanghai ARWU, THE Impact Rankings, US College Navigator (IPEDS), and Stanford Online courses in parallel, returning every match in one consistent dataset. No API keys, no manual copy-paste, a single keyword and the sources you care about.

Who uses it	What they scrape University Rankings Mega Pack for
Academic researchers	Comparing how a university performs across ARWU, THE Impact, and IPEDS metrics in one dataset.
University marketing teams	Monitoring competitor institutions' rankings and online course offerings to benchmark their own programs.
Education consultants	Building a complete profile of a client's target schools with rankings, costs, and available online courses.
Prospective graduate students	Filtering universities by research ranking, social impact, and available online courses in their field.

What it does

This Actor collects university rankings, institutional details, and online course listings from four global sources and returns each university as a flat row.

• 🏛️ Four sources, one query: Shanghai ARWU, THE Impact Rankings, US College Navigator, and Stanford Online queried in parallel from a single keyword.
• 🔍 Keyword-driven search: A free-text keyword filters university names across all selected sources, so you get only relevant institutions.
• 📊 Per-source caps: Set a maximum number of universities to collect from each source, keeping runs predictable and fast.
• 📦 Flat row output: Every university, regardless of source, lands in your dataset as one row with a fixed schema for easy analysis.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with University Rankings Mega Pack data

📈 Build a multi-ranking comparison dataset.

A higher education researcher enters a broad keyword like 'engineering' and collects ARWU, THE Impact, and IPEDS data for the top 100 universities per source, then analyzes correlation between research output and social impact scores.

🎓 Find universities offering online courses in a specific field.

A prospective student searches for 'data science' with only the Stanford Online source enabled, collecting every relevant course listing to compare curricula, instructors, and availability before applying.

🏫 Benchmark your institution against peers.

A university marketing director runs a query for competitor institution names across all four sources, pulling rankings, enrollment data, and online course counts to inform a strategic positioning report.

🌍 Identify globally ranked institutions in a niche discipline.

An education consultant searches for 'marine biology' and collects ARWU and THE Impact results to build a shortlist of top-ranked programs for a client seeking international graduate school options.

Why choose this scraper

	What you get
One keyword, four datasets	Query Shanghai, THE, IPEDS, and Stanford Online simultaneously and get results in one unified schema.
No API registration	Reads public ranking pages and course catalogs directly, with no OAuth, no developer app, and no rate-limit headaches.
Parallel source execution	Each selected source runs concurrently, so a four-source query completes in roughly the time of the slowest single source.
Flexible source selection	Run all four sources or pick one; the Actor adapts to whatever comparison you need that day.

How it compares

No other Store actor targets University Rankings Mega Pack the same way, so the honest comparison is with the alternatives teams actually weigh.

	University Rankings Mega Pack Scraper	Build it in-house	By hand
Setup	Run it now, zero config	Days of engineering	None, but hours per pull
When University Rankings Mega Pack changes	Maintained for you	You fix it	You re-learn the page
Proxies, retries, anti-bot	Built in	Your problem	Browser only
Output	Fixed JSON schema, CSV/Excel export	Whatever you build	Copy-paste
Cost	Pay per result	Engineering time	Analyst hours

Configure the run

Drive the Actor with a university name or keyword and select which sources to query; each source returns up to the maximum you set, so only the most relevant institutions reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
 "query": "engineering",
 "maxItems": 10,
 "sources": [
 "shanghai",
 "the-impact",
 "ed-college-navigator",
 "stanford"
 ]
}

A larger pull:

{
 "query": "engineering",
 "maxItems": 200,
 "sources": [
 "shanghai",
 "the-impact",
 "ed-college-navigator",
 "stanford"
 ]
}

Pricing

Pay-per-result: $0.021 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$2.10
1,000 results	$21.00
10,000 results	$210.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the University Rankings Mega Pack Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to University Rankings Mega Pack through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/university-rankings-mega-pack-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results for my keyword?

The keyword is applied as a substring filter on university names. Try a broader term like 'technology' instead of a very specific phrase. Also check that you have at least one source selected in the sources array.

Why does my run return fewer universities than the maxItems I set?

The Actor stops when a source runs out of matching results. If your keyword is narrow, there may be fewer universities that match. Try a broader keyword or increase maxItems if you suspect more results exist.

Why does the Stanford Online source return different fields than the ranking sources?

Stanford Online is a course catalog, not a ranking system, so its data shape differs. The Actor normalizes what it can into a shared schema, but course-specific fields like instructor and course title will be populated only for Stanford results.

Why did my run time out?

If you set a very high maxItems across all four sources, the run may exceed the default timeout. Reduce maxItems, select fewer sources, or increase the run timeout in the Actor's advanced settings.

Why are some ranking scores missing in my output?

Not every ranking source publishes the same metrics. Shanghai ARWU includes scores like alumni awards and highly cited researchers, while THE Impact focuses on SDG alignment. Missing values mean that metric is not published by that source for that university.

FAQ

Question	Answer
Which ranking sources does this Actor cover?	It queries four sources: Shanghai ARWU (Academic Ranking of World Universities), THE Impact Rankings, US College Navigator (IPEDS data from NCES), and Stanford Online course listings. You can select any combination of these per run.
Can I scrape only one source, like Shanghai ARWU?	Yes. The sources input is a multi-select array. Uncheck the sources you do not need and the Actor will query only the ones you leave selected.
What does the keyword search match against?	For Stanford Online, the keyword is used as an explore search term. For College Navigator, it filters institution names as a substring. For Shanghai and THE, it filters university names as a substring match.
How many universities can I collect per run?	You set the maxItems value, which applies per source. If you set 100 and select all four sources, you can collect up to 400 universities total. The maximum is 1,000,000 per source.
Does this Actor require API keys or login credentials?	No. It reads publicly available ranking pages and course catalogs directly. There is no OAuth flow, no developer app registration, and no API key to manage.
What output formats are supported?	The Actor outputs to Apify's default dataset, which you can export as CSV, JSON, Excel, XML, or RSS. The schema is consistent regardless of which sources you query.
How long does a run take with all four sources?	The sources run in parallel, so total runtime is roughly the duration of the slowest single source. A typical run collecting 10 universities per source completes in under a minute.
Can I schedule this Actor to run weekly?	Yes. Apify supports scheduled runs via cron expressions. Set it to run weekly or monthly to track ranking changes over time without manual intervention.
Does the Actor handle pagination automatically?	Yes. Each source's scraper handles its own pagination internally. You only set the maximum number of universities you want per source, and the Actor pages until it reaches that count or exhausts results.
What data fields does the Actor return?	The exact fields depend on which sources you select, but the dataset includes university name, rank, scores, location, website, and for Stanford Online, course titles and instructors. All rows share a unified schema.

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🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by the respective data sources. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.