COMPANYAI API MCP READY

Glassdoor Reviews API

Collect Glassdoor company reviews as clean, structured JSON for employer-brand and HR analytics. Send one or many company URLs and get overall and category ratings, pros and cons, employment type, and dates. Reliable, pay per review, MCP-ready for Claude and AI agents.

MEDIAN LAGon demand
PARAMETERS3
TOTAL USERS4
MONTHLY ACTIVE4
TOTAL RUNS49
RUNS SUCCEEDED97.0%
RATINGno ratings yet

Input parameters

PARAMETERTYPEREQDEFAULTDESCRIPTION
companyUrls string[] yes — One or more Glassdoor company review URLs, e.g. https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm.
maxReviewsPerCompany integer no 100 Maximum number of reviews to return per company (1-1000).
days integer no 30 How many days of reviews to collect, e.g. 30.

Worked examples

Basic — the required input, with the schema's own example values
{
  "companyUrls": [
    "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"
  ]
}

Tasks

Saved runs with the inputs already filled in — each one a standalone page and a working configuration example.

Request a task →

Code

curl

curl -X POST "https://api.apify.com/v2/acts/johnvc~glassdoor-reviews-api/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"companyUrls": ["https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"]}'

Python

from apify_client import ApifyClient

client = ApifyClient("APIFY_TOKEN")
run = client.actor("johnvc/glassdoor-reviews-api").call(
    run_input={'companyUrls': ['https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm']}
)
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)