GreatSchools Scraper — Ratings & Demographics

Extract comprehensive US K-12 school data from GreatSchools.org — the nation's leading school quality resource trusted by millions of parents and educators.

What it does

The GreatSchools Scraper collects detailed school profiles for public, charter, and private schools across all 50 US states plus Washington DC. Search by city/state or paste GreatSchools URLs directly. Each record includes 35+ data fields: GreatSchools ratings (1-10), test score ratings, student progress ratings, community review ratings, enrollment numbers, grade levels, contact information (phone, website, principal email), student demographics (race/ethnicity, gender breakdown, low-income percentage), regular attendance rates, Title I status, equity indicators, nearby schools, and recent community reviews.

Use cases

• Real estate analysis — school quality overlays for neighborhood scoring and property valuation
• Relocation research — side-by-side school comparisons for families moving to a new city
• Lead generation — principal contact lists for EdTech sales, partnership outreach, and marketing campaigns
• Education research — demographics analysis, equity studies, and test score benchmarking by district
• Data enrichment — school intelligence for dashboards, AI/ML datasets, and market sizing reports
• Nonprofit & journalism — public school data for transparency projects and investigative reporting

Input parameters

Field	Type	Required	Default	Description
startUrls	array	No	—	GreatSchools.org URLs to scrape directly (school profiles or city listing pages)
location	string	No*	Orlando, FL	City and US state in City, ST format (e.g. Chicago, IL)
schoolLevels	array	No	—	Filter by level: preschool, elementary, middle, high
schoolTypes	array	No	—	Filter by type: public, charter, private
maxResults	integer	No	10	Maximum number of schools to collect
maxConcurrency	integer	No	5	Concurrent request limit
proxyConfiguration	object	No	—	Proxy settings (datacenter by default)

*Either startUrls or location must be provided.

Output fields

Field	Type	Example
schoolId	string|null	"18885"
gsid	string|null	"FL-18885"
name	string	"Laureate Park Elementary"
url	string|null	"https://www.greatschools.org/florida/orlando/18885-Laureate-Park-Elementary/"
state	string|null	"FL"
city	string|null	"Orlando"
county	string|null	"Orange County"
districtName	string|null	"Orange County Public Schools"
districtUrl	string|null	"https://www.greatschools.org/florida/orlando/orange-county-public-schools/"
schoolType	string|null	"public"
gradeLevels	string|null	"PK,KG,1,2,3,4,5"
grades	string|null	"PK, K-5"
greatSchoolsRating	integer|null	10
testScoreRating	integer|null	10
studentProgressRating	integer|null	10
reviewRating	number|null	2.92
reviewCount	integer|null	12
enrollment	integer|null	778
studentTeacherRatio	string|null	"15:1"
address	string|null	"7800 Laureate Boulevard"
zipCode	string|null	"32827"
phone	string|null	"(407) 730-8730"
website	string|null	"http://laureateparkes.ocps.net/"
schoolLeader	string|null	"Mr Jose Perez-Valentin"
schoolLeaderEmail	string|null	"25704@OCPS.NET"
lowIncomePercent	number|null	19.3
ethnicity	array	[{"breakdown":"Hispanic","percent":38.3}]
genderBreakdown	array	[{"gender":"Male","schoolPercent":52.05}]
regularAttendancePercent	number|null	90
titleI	boolean|null	false
equityIndicator	boolean|null	true
collegeSuccessAwards	array	[]
claimStatus	string|null	"unclaimed"
description	string|null	"Laureate Park Elementary is a public school..."
nearbySchools	array	[{"name":"Luminary Middle","rating":9,"distanceMiles":1.04}]
reviews	array	[{"date":"2026-05-21","rating":2,"text":"..."}]
scrapedAt	string	"2026-07-01T12:00:00.000Z"
sourceUrl	string	"https://www.greatschools.org/florida/orlando/18885-..."

Pricing

Event	Price	Description
Actor Start	$0.005	Charged once when the run starts
School Scraped	$0.012 per result	Charged for each school record with full profile data

Example cost: Scraping 100 schools = $0.005 + (100 x $0.012) = $1.21

How it works

1. Search mode — Enter a city and state (e.g. Orlando, FL). The actor constructs the GreatSchools city page URL and extracts all school profile links from it.
2. URL mode — Paste GreatSchools URLs directly (school profiles or city listing pages).
3. The actor visits each school profile page and extracts data from embedded JSON (gon object), JSON-LD schema, and the HTML DOM.
4. Filters by school level and type are applied after extraction.
5. Results are pushed to the dataset immediately — no buffering, no data loss on timeout.

Technical details

• Crawler: CheerioCrawler (static HTML parsing — no browser needed, fast and reliable)
• Data extraction: Parses the gon JavaScript object embedded in <script> tags for structured data (ratings, demographics, enrollment), plus JSON-LD School schema for address, phone, website, and reviews
• Proxy: Datacenter proxies by default. Switch to residential if you encounter blocking.
• Deduplication: Schools are deduplicated by GreatSchools ID across multiple listing pages

API usage

# Run via API
curl -X POST "https://api.apify.com/v2/acts/USERNAME~greatschools-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"location": "Orlando, FL", "maxResults": 50}'

// Run via JavaScript SDK
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('USERNAME/greatschools-scraper').call({
    location: 'Orlando, FL',
    maxResults: 50,
    schoolTypes: ['public', 'charter'],
});
const dataset = await client.dataset(run.defaultDatasetId).listItems();
console.log(dataset.items);

Limitations

• GreatSchools city pages list schools from the "Top Rated Schools" section, which may not include every school in a city. For comprehensive coverage, use the startUrls field with specific school profile URLs.
• Some data fields (test score breakdowns, course lists) are loaded via JavaScript and may not be available in the static HTML. The actor captures all data available in the server-rendered page.
• Private school profiles may have less data than public schools (fewer ratings, no test scores).

What is GreatSchools Scraper?

GreatSchools Scraper turns the target data into structured, reusable results on Apify. Use it when you need repeatable collection for researchers, analysts, education or recruiting teams, and structured-data workflows without maintaining a custom scraper or one-off integration. Run it manually, schedule recurring jobs, call it through the Apify API, or connect it to an AI agent through the Apify MCP server.

The Actor stores results in an Apify dataset, where they can be previewed and exported as JSON, CSV, Excel, XML, or RSS. Availability and completeness depend on the source, supplied inputs, public visibility, authentication requirements, and upstream rate limits.

Use cases for GreatSchools Scraper

• Build structured datasets for research, reporting, enrichment, or monitoring.
• Automate repetitive collection with schedules, webhooks, and API calls.
• Feed clean records into spreadsheets, databases, CRMs, BI tools, AI agents, or RAG pipelines.
• Track changes over time by running the same validated input on a schedule.
• Replace fragile manual copy-and-paste work with a reproducible Apify workflow.

How to use GreatSchools Scraper

1. Open the Actor input page and choose a focused, valid target.
2. Set a conservative result limit for the first run.
3. Start the Actor and inspect the dataset for coverage and field availability.
4. Export the results or connect the dataset to your downstream system.
5. Scale gradually and use scheduling, pagination, or proxies when supported.

Important input options

• startUrls — Use this field when the user provides specific GreatSchools.org URLs to scrape directly. Accepts school profile URLs (e.g. https://www.greatschools.org/florida/orlando/18885-Laureate-Park-El
• location — Enter a city and US state to search for schools. Use 'City, ST' format — for example, 'Orlando, FL' or 'Los Angeles, CA'. You can also use just a city name with full state like 'Oklahoma Cit
• schoolLevels — Select school levels to filter by. Leave empty to include all levels. Valid values: preschool, elementary, middle, high. The actor checks each school's grade range and includes only matching
• schoolTypes — Select school types to filter by. Leave empty to include all types. Valid values: public, charter, private.
• maxResults — Maximum number of schools to collect and return. Set to a small number (3-5) first to verify data quality before scaling up. A single city page typically lists 100-200+ schools.
• proxyConfiguration — Select a proxy to use for scraping. The actor works with datacenter proxies by default. If GreatSchools blocks your requests, switch to residential proxies or provide a custom proxy URL.
• maxConcurrency — Maximum number of concurrent requests. Lower this if you encounter rate limiting or timeouts. Default is 5 which balances speed and reliability.

API and automation example

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('muhammadafzal/greatschools-scraper').call({
  // Add the same input fields you use in the Apify Console.
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

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Frequently asked questions

How many results can I scrape with GreatSchools Scraper?

The practical total depends on the source, input limits, pagination, available records, run timeout, and upstream restrictions. Start with a small run, verify the output, and increase the limit gradually.

Can I integrate GreatSchools Scraper with other apps?

Yes. Use Apify integrations, webhooks, schedules, dataset exports, Make, Zapier, Google Sheets, cloud storage, or your own application.

Can I use GreatSchools Scraper with the Apify API?

Yes. Start runs with the Apify REST API or an official Apify client, then retrieve records from the run's default dataset. Keep your API token in a secret or environment variable.

Can I use GreatSchools Scraper through an MCP Server?

Yes. The Apify MCP server can expose the Actor to compatible AI clients and agents. Review the input and expected cost before allowing an autonomous workflow to run it at scale.

Do I need proxies?

It depends on the source and volume. Use the default configuration first. For larger or geographically sensitive jobs, select an appropriate proxy configuration only when the Actor supports it.

Is it legal to scrape this data?

Scraping rules vary by source, jurisdiction, data type, and intended use. Collect only data you are authorized to access, respect applicable terms and privacy laws, and avoid restricted or personal data misuse. This documentation is not legal advice.

Your feedback

If a field is missing, a source layout has changed, or you need a supported use case documented, open an issue on the Actor page with a reproducible input and run ID.