# Apify Actor Comparison Report (`agentictools/actor-comparison`) Actor Compare two or more Apify Actors side by side on usage, ratings, pricing, and freshness. - **URL**: https://apify.com/agentictools/actor-comparison.md - **Developed by:** [Ken Agland](https://apify.com/agentictools) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $1.00 / 1,000 actor compareds 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 ## Apify Actor Comparison Report Compare two or more Apify Actors side by side on usage, ratings, pricing, and freshness. ### What it does - Takes a list of Actors (by `username/name` or ID), or a search term with a limit. - Returns one normalized dataset item per Actor with the same flat set of fields. - Names the winner per metric in the run OUTPUT: most users, top rated, cheapest, most runs, freshest. - Uses the public Apify API. No API key needed to run it here. ### Example input Compare specific Actors: ```json { "actors": [ "apify/instagram-scraper", "apify/instagram-profile-scraper", "clockworks/tiktok-scraper" ] } ```` Compare the top matches for a search: ```json { "search": "tiktok", "limit": 5, "enrich": true } ``` ### Input | Field | Type | Description | |---|---|---| | `actors` | array | Actors to compare, each as `username/name` or an Actor ID. Provide this or `search`. | | `search` | string | Search term. When set and no `actors` list is given, the top Store matches are compared. | | `limit` | integer | How many top matches to compare when using `search`. Default 5, max 100. | | `enrich` | boolean | Add each Actor's last modified date. Default true. | If both `actors` and `search` are given, `actors` wins. ### Output Each dataset item is one Actor: ```json { "fullName": "apify/instagram-scraper", "title": "Instagram Scraper", "totalUsers": 318106, "totalRuns": 154178225, "reviewRating": 4.74, "reviewCount": 477, "pricingModel": "PAY_PER_EVENT", "priceUsd": 0.0027, "successRate30DaysPct": 99.6, "lastModified": "2026-07-04T14:41:00.207Z", "bookmarks": 4057 } ``` The run's `OUTPUT` record in the default key-value store names the winner per metric: ```json { "input": { "actors": [ "apify/instagram-scraper", "clockworks/tiktok-scraper" ], "search": null, "limit": 5, "enrich": true }, "compared": 2, "winners": { "mostUsers": "apify/instagram-scraper", "topRated": "clockworks/tiktok-scraper", "cheapest": "apify/instagram-scraper", "mostRuns": "apify/instagram-scraper", "freshest": "apify/instagram-scraper" }, "generatedFrom": "https://api.apify.com/v2/acts" } ``` ### How it works For an `actors` list, the Actor fetches each Actor's detail endpoint, which carries stats, pricing, and the last modified date. For a `search`, it queries the Store search endpoint, which returns stats and pricing inline, then takes the top `limit` matches and (when `enrich` is true) fetches the last modified date for each. All records are normalized to the same fields, the winner per metric is chosen, and both the dataset and the `OUTPUT` summary are written. It uses the run's `APIFY_TOKEN` for higher rate limits, with no configuration needed. MIT licensed. # Actor input Schema ## `actors` (type: `array`): List of Actors to compare, each as "username/name" (for example "apify/instagram-scraper") or an Actor ID. Provide this or a search term. ## `search` (type: `string`): Full-text search term. When set and no Actors list is given, the top matches from the Apify Store are compared. Ignored when an Actors list is provided. ## `limit` (type: `integer`): How many top matches to compare when using a search query. Ignored when an Actors list is provided. ## `enrich` (type: `boolean`): Add each Actor's last modified date. For the search path this makes one extra API call per Actor. Actors fetched by name already include the date. ## Actor input object example ```json { "actors": [ "apify/instagram-scraper", "apify/instagram-profile-scraper", "clockworks/tiktok-scraper" ], "search": "tiktok", "limit": 5, "enrich": true } ``` # 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 = { "actors": [ "apify/instagram-scraper", "apify/instagram-profile-scraper", "clockworks/tiktok-scraper" ] }; // Run the Actor and wait for it to finish const run = await client.actor("agentictools/actor-comparison").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 = { "actors": [ "apify/instagram-scraper", "apify/instagram-profile-scraper", "clockworks/tiktok-scraper", ] } # Run the Actor and wait for it to finish run = client.actor("agentictools/actor-comparison").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 '{ "actors": [ "apify/instagram-scraper", "apify/instagram-profile-scraper", "clockworks/tiktok-scraper" ] }' | apify call agentictools/actor-comparison --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agentictools/actor-comparison", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apify Actor Comparison Report", "description": "Compare two or more Apify Actors side by side on usage, ratings, pricing, and freshness.", "version": "0.1", "x-build-id": "LKYOqkNwnGu8hbtzk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agentictools~actor-comparison/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agentictools-actor-comparison", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agentictools~actor-comparison/runs": { "post": { "operationId": "runs-sync-agentictools-actor-comparison", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agentictools~actor-comparison/run-sync": { "post": { "operationId": "run-sync-agentictools-actor-comparison", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "actors": { "title": "Actors to compare", "type": "array", "description": "List of Actors to compare, each as \"username/name\" (for example \"apify/instagram-scraper\") or an Actor ID. Provide this or a search term.", "items": { "type": "string" } }, "search": { "title": "Search query", "type": "string", "description": "Full-text search term. When set and no Actors list is given, the top matches from the Apify Store are compared. Ignored when an Actors list is provided." }, "limit": { "title": "Number of Actors from search", "minimum": 1, "maximum": 100, "type": "integer", "description": "How many top matches to compare when using a search query. Ignored when an Actors list is provided.", "default": 5 }, "enrich": { "title": "Add last modified date", "type": "boolean", "description": "Add each Actor's last modified date. For the search path this makes one extra API call per Actor. Actors fetched by name already include the date.", "default": true } } }, "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 } } } } } } } } } } ```