# Apify Store Intelligence – Trends, Revenue & Rankings (`dev-sinior/apify-store-intel`) Actor Scrape the entire Apify Store to discover top actors, estimate monthly revenues, detect trending bots and analyze the competitive landscape. Perfect for market research and finding untapped niches. - **URL**: https://apify.com/dev-sinior/apify-store-intel.md - **Developed by:** [DEV-SINIOR](https://apify.com/dev-sinior) (community) - **Categories:** Automation, E-commerce, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README undefined # Actor input Schema ## `search` (type: `string`): Keyword to search in actor names and descriptions (leave empty for all). ## `category` (type: `string`): Filter by Apify Store category (e.g. 'SCRAPING', 'AI', 'ECOMMERCE'). ## `pricingModel` (type: `string`): Filter by pricing model. ## `maxActors` (type: `integer`): Maximum number of actors to collect and save. ## `minUsers` (type: `integer`): Only include actors with at least this many total users. ## `minRuns` (type: `integer`): Only include actors with at least this many total runs. ## `onlyTrending` (type: `boolean`): If enabled, only return actors detected as fast-growing / trending. ## `trendingMinUsers` (type: `integer`): Minimum users for an actor to be considered trending. ## `sortBy` (type: `string`): How to rank the results. ## `sortOrder` (type: `string`): Sort direction: descending (highest first) or ascending (lowest first). ## `includeCategories` (type: `array`): Leave empty for all. Example: ['ECOMMERCE', 'AI'] ## `excludeCategories` (type: `array`): Categories to skip. ## `excludeAuthors` (type: `array`): Author usernames to exclude (e.g. 'apify' to skip official actors). ## Actor input object example ```json { "search": "amazon scraper", "category": "ECOMMERCE", "pricingModel": "", "maxActors": 500, "minUsers": 0, "minRuns": 0, "onlyTrending": false, "trendingMinUsers": 50, "sortBy": "totalUsers", "sortOrder": "desc", "excludeAuthors": [] } ```` # Actor output Schema ## `rank` (type: `string`): Position in the sorted results. ## `author` (type: `string`): Apify username of the actor creator. ## `title` (type: `string`): Display title of the actor. ## `categories` (type: `string`): Apify Store categories. ## `pricingModel` (type: `string`): FREE, PAY\_PER\_RESULT, FLAT\_PRICE\_PER\_MONTH or PAY\_PER\_RUN. ## `totalUsers` (type: `string`): Cumulative number of users who used this actor. ## `totalRuns` (type: `string`): Total number of times the actor has been run. ## `estimatedMonthlyRevUsd` (type: `string`): Estimated monthly revenue in USD (heuristic calculation). ## `isTrending` (type: `string`): True if the actor shows fast user growth relative to its age. ## `rating` (type: `string`): Average user rating. ## `createdAt` (type: `string`): Date the actor was first published. ## `url` (type: `string`): Link to the actor on Apify Store. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("dev-sinior/apify-store-intel").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("dev-sinior/apify-store-intel").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call dev-sinior/apify-store-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dev-sinior/apify-store-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apify Store Intelligence – Trends, Revenue & Rankings", "description": "Scrape the entire Apify Store to discover top actors, estimate monthly revenues, detect trending bots and analyze the competitive landscape. Perfect for market research and finding untapped niches.", "version": "1.0", "x-build-id": "LQLVnDX1WAbnELwrd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dev-sinior~apify-store-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dev-sinior-apify-store-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dev-sinior~apify-store-intel/runs": { "post": { "operationId": "runs-sync-dev-sinior-apify-store-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dev-sinior~apify-store-intel/run-sync": { "post": { "operationId": "run-sync-dev-sinior-apify-store-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "search": { "title": "Search Query", "type": "string", "description": "Keyword to search in actor names and descriptions (leave empty for all)." }, "category": { "title": "Category Filter", "type": "string", "description": "Filter by Apify Store category (e.g. 'SCRAPING', 'AI', 'ECOMMERCE')." }, "pricingModel": { "title": "Pricing Model Filter", "enum": [ "", "FREE", "PAY_PER_RESULT", "FLAT_PRICE_PER_MONTH", "PAY_PER_RUN" ], "type": "string", "description": "Filter by pricing model.", "default": "" }, "maxActors": { "title": "Max Actors to Collect", "minimum": 10, "maximum": 5000, "type": "integer", "description": "Maximum number of actors to collect and save.", "default": 500 }, "minUsers": { "title": "Minimum Users", "minimum": 0, "type": "integer", "description": "Only include actors with at least this many total users.", "default": 0 }, "minRuns": { "title": "Minimum Total Runs", "minimum": 0, "type": "integer", "description": "Only include actors with at least this many total runs.", "default": 0 }, "onlyTrending": { "title": "Trending Actors Only", "type": "boolean", "description": "If enabled, only return actors detected as fast-growing / trending.", "default": false }, "trendingMinUsers": { "title": "Trending: Min Users Threshold", "minimum": 1, "type": "integer", "description": "Minimum users for an actor to be considered trending.", "default": 50 }, "sortBy": { "title": "Sort By", "enum": [ "totalUsers", "totalRuns", "estimatedRevenue", "createdAt" ], "type": "string", "description": "How to rank the results.", "default": "totalUsers" }, "sortOrder": { "title": "Sort Order", "enum": [ "desc", "asc" ], "type": "string", "description": "Sort direction: descending (highest first) or ascending (lowest first).", "default": "desc" }, "includeCategories": { "title": "Include Only These Categories", "type": "array", "description": "Leave empty for all. Example: ['ECOMMERCE', 'AI']", "items": { "type": "string" } }, "excludeCategories": { "title": "Exclude These Categories", "type": "array", "description": "Categories to skip.", "items": { "type": "string" } }, "excludeAuthors": { "title": "Exclude These Authors", "type": "array", "description": "Author usernames to exclude (e.g. 'apify' to skip official actors).", "default": [], "items": { "type": "string" } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```