DEVELOPER TOOLS API MCP READY

Apify Store API

Apify Store API - extract every public Actor's pricing, usage trends, success rate, ratings, and categories as structured JSON. Filter by keyword, category, pricing model, or developer, or sweep the whole store. For market research, competitor tracking, and AI agents.

MEDIAN LAGon demand

PARAMETERS8

TOTAL USERS9

MONTHLY ACTIVE7

TOTAL RUNS102

RUNS SUCCEEDED100.0%

RATINGno ratings yet

Input parameters

PARAMETER	TYPE	REQ	DEFAULT	DESCRIPTION
search	string	no	—	Filter Actors by keyword across title, name, description, developer, and README (e.g. 'instagram', 'pdf', 'maps').
category	enum	no	—	Return only Actors in this Apify Store category.
pricingModel	enum	no	—	Return only Actors on this pricing model.
username	string	no	—	Return only Actors published by this developer handle (e.g. 'apify', 'johnvc').
sortBy	enum	no	relevance	Order the results. 'relevance' (default), 'popularity' (most users first), 'newest', or 'lastUpdate'.
maxItems	integer	no	1000	Maximum number of Actors to return.
offset	integer	no	0	Skip this many Actors before returning results.
includeDetails	boolean	no	False	Enrich each Actor with its full README and input schema (1-2 extra API calls per Actor).

Worked examples

Basic — the required input, with the schema's own example values

{
  "search": "example",
  "category": "example"
}

Coverage

25

category — AI AGENTS AUTOMATION BUSINESS COVID_19 +20

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~store-actor-intelligence-api/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"search": "example", "category": "example"}'

Python

from apify_client import ApifyClient

client = ApifyClient("APIFY_TOKEN")
run = client.actor("johnvc/store-actor-intelligence-api").call(
    run_input={'search': 'example', 'category': 'example'}
)
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)