# Adobe Stock Scraper - Low-costπŸ’²πŸ”₯🎨 (`delectable_incubator/adobe-stock-scraper---low-cost`) Actor Scrape Adobe Stock media data by keyword 🎨. Extract asset titles, content types, thumbnails, download URLs, license details, and metadata. Ideal for stock content analysis, creative research, and building structured datasets for design, marketing, and media projects πŸ“ŠπŸš€ - **URL**: https://apify.com/delectable\_incubator/adobe-stock-scraper---low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** Videos, Social media, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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

Adobe Stock Search Scraper - PrimeScrape

--- ### Adobe Stock Search Scraper πŸ”πŸŽ¨πŸ–ΌοΈ The Adobe Stock Search Scraper is a fast, reliable, and scalable automation tool designed to extract structured media asset data directly from Adobe Stock. It converts search results into clean, structured datasets ready for creative research, content discovery, asset analysis, and media intelligence. --- ### Adobe Stock Scraper πŸŽ¨πŸ”ŽπŸ–ΌοΈ This scraper automatically extracts structured media listings from Adobe Stock search result pages. Ideal for designers, marketers, content researchers, and creative professionals. --- ### 🎯 What This Scraper Does Simply provide search parameters such as keywords, content type, or filters, and the scraper will automatically extract structured media data. βœ… Extracts Adobe Stock media assets βœ… Supports keyword-based search βœ… Handles pagination automatically βœ… Respects maxitems limits βœ… Cleans and structures media data βœ… Ready for analytics and integrations --- ### πŸ“Š Data Extracted πŸ–ΌοΈ Media Asset Fields | Field | Description | | -------------------- | ------------------------------- | | πŸ†” `content_id` | Unique content identifier | | πŸ“ `title` | Asset title | | πŸ–Ό `content_type` | Media type (image, video, etc.) | | πŸ–Ό `thumbnail_url` | Preview image | | 🌐 `content_url` | Asset page URL | | ✍️ `author` | Creator name | | πŸ”’ `creator_id` | Creator identifier | | πŸ“₯ `download_url` | Download / preview URL | | πŸ’³ `premium_level` | License tiers | | 🏷️ `category` | Asset category | | πŸ”— `asset_type` | Asset type | | πŸ“œ `license_details` | Licensing information | --- ### πŸ›  How to Use 1️⃣ Configure Input Provide one or more AWS Marketplace search URLs: ```` { "keyword": "ai", "sort\_by": "Relevance", "types": "All", "maxitems": 200 } ``` 2️⃣ Run the Actor The scraper will: β€’ Perform keyword-based search β€’ Automatically paginate results β€’ Extract structured media assets β€’ Stop when maxitems is reached 3️⃣ Export the Dataset Download your results in multiple formats: βœ… JSON βœ… CSV βœ… Excel βœ… XML βœ… HTML --- ### βš™οΈ Input Configuration #### πŸ“₯ Input Example ``` { "keyword": "ai", "sort\_by": "Relevance", "types": "All", "maxitems": 200 } ``` #### Input Fields | Field | Type | Description | | ---------- | ------- | --------------------------------- | | `keyword` | array | Bulk Search keyword | | `sort_by` | string | Sorting option (e.g., Relevance) | | `types` | string | Content type (image, video, etc.) | | `maxitems` | integer | Maximum results to extract | --- ### πŸ“€ Output Example ``` { "content\_id": 323829966, "title": "AI, Machine learning, Hands of robot...", "content\_type": "image/jpeg", "thumbnail\_url": "https://t4.ftcdn.net/image.jpg", "content\_url": "https://stock.adobe.com/image/323829966", "author": "ipopba", "creator\_id": 205024019, "download\_url": "https://stock.adobe.com/download/323829966", "asset\_type": "Image", "category": "Science" } ```` --- ### πŸ“Š Output explanation | Field | Description | | ----------------- | ----------------------- | | `content_id` | Unique content ID | | `title` | Asset title | | `content_type` | Media type | | `thumbnail_url` | Preview image | | `content_url` | Asset page URL | | `author` | Creator name | | `creator_id` | Creator identifier | | `download_url` | Download or preview URL | | `asset_type` | Asset type | | `category` | Asset category | | `license_details` | Licensing information | --- ### 🌍 Why Use This Scraper? 🎨 Creative Discovery β€” Find images, videos, and design assets πŸ“Š Content Analysis β€” Analyze trends in creative media 🏷️ Asset Categorization β€” Filter by type and category πŸ“ˆ Market Insights β€” Track popular design trends πŸ€– Data & AI β€” Build datasets for ML or automation ⚑ Scalable β€” Designed for high-volume extraction --- ### ⚠️ Disclaimer This tool is an independent solution and is not affiliated with or endorsed by Adobe Stock. --- ### πŸ’Έ Pricing This scraper runs on a **pay per events subscription model**. You only pay for **successful runs**. πŸ’³ **Price:** $2.89 / 1000 results --- ### Related Actors If you're interested in other German πŸ‡©πŸ‡ͺ, Austrian πŸ‡¦πŸ‡Ή, Swiss πŸ‡¨πŸ‡­, or Dach or European πŸ‡ͺπŸ‡Ί scrapers, explore more scrapers across Europe πŸ‡©πŸ‡ͺπŸ‡ͺπŸ‡Ί (Coming soon) --- ### πŸ“¬ Support ⭐⭐⭐⭐⭐ Leave a 5-star rating if you like this tool --- ### 🌍 PrimeScrape Built for scalable web data extraction & automation Contact for custom scraping solutions or enterprise requests via Apify or by email. # Actor input Schema ## `keywords` (type: `array`): Enter one or more keywords to search on Adobe Stock. Each keyword will be scraped separately. Example: ["nature", "city", "abstract"]. ## `sort_by` (type: `string`): Choose how you want to sort the search results: by relevance, most recent, or by number of downloads πŸ“Š. ## `types` (type: `string`): Select the type of assets to search for on Adobe Stock: Images, Videos, Templates, or All asset types πŸŽ¨πŸ”. ## `maxitems` (type: `integer`): Set the maximum number of asset listings to scrape per keyword πŸ“Š. ## Actor input object example ```json { "keywords": [ "3D" ], "sort_by": "Relevance", "types": "All", "maxitems": 150 } ```` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "keywords": [ "3D" ], "sort_by": "Relevance", "types": "All", "maxitems": 150 }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/adobe-stock-scraper---low-cost").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "keywords": ["3D"], "sort_by": "Relevance", "types": "All", "maxitems": 150, } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/adobe-stock-scraper---low-cost").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "3D" ], "sort_by": "Relevance", "types": "All", "maxitems": 150 }' | apify call delectable_incubator/adobe-stock-scraper---low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/adobe-stock-scraper---low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Adobe Stock Scraper - Low-costπŸ’²πŸ”₯🎨", "description": "Scrape Adobe Stock media data by keyword 🎨. Extract asset titles, content types, thumbnails, download URLs, license details, and metadata. Ideal for stock content analysis, creative research, and building structured datasets for design, marketing, and media projects πŸ“ŠπŸš€", "version": "0.0", "x-build-id": "GA0UiklyxdABJPlWN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~adobe-stock-scraper---low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-adobe-stock-scraper---low-cost", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~adobe-stock-scraper---low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-adobe-stock-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~adobe-stock-scraper---low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-adobe-stock-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "keywords" ], "properties": { "keywords": { "title": "Keywords to search for πŸŽ¨πŸ”", "type": "array", "description": "Enter one or more keywords to search on Adobe Stock. Each keyword will be scraped separately. Example: [\"nature\", \"city\", \"abstract\"].", "default": [ "3D" ], "items": { "type": "string" } }, "sort_by": { "title": "Sort results by πŸ“Š", "enum": [ "Relevance", "Most recent", "Downloads" ], "type": "string", "description": "Choose how you want to sort the search results: by relevance, most recent, or by number of downloads πŸ“Š.", "default": "Relevance" }, "types": { "title": "Asset types", "enum": [ "All", "Images", "Videos", "Templates" ], "type": "string", "description": "Select the type of assets to search for on Adobe Stock: Images, Videos, Templates, or All asset types πŸŽ¨πŸ”.", "default": "All" }, "maxitems": { "title": "Maximum number of assets per keyword πŸ“Š", "type": "integer", "description": "Set the maximum number of asset listings to scrape per keyword πŸ“Š.", "default": 150 } } }, "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 } } } } } } } } } } ```