# Instagram Reels Thumbnail Scraper (`codenest/instagram-reels-thumbnail-scraper`) Actor Extract high-quality thumbnails from Instagram Reels! This scraper delivers multiple preview images with full metadata, engagement stats, and secure Apify KV storage URLs. Perfect for marketers 📈, researchers 🔍, and developers 📱 analysing visual content trends. Instagram Reels Thumbnail Scraper. - **URL**: https://apify.com/codenest/instagram-reels-thumbnail-scraper.md - **Developed by:** [CodeNest](https://apify.com/codenest) (community) - **Categories:** Social media, Developer tools, Other - **Stats:** 22 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $5.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## Instagram Reels Thumbnail Scraper - Professional Thumbnail Extraction Tool **🚀 Effortlessly extract high-quality thumbnails from Instagram Reels with our enterprise-grade Instagram Reels Thumbnail Scraper! This powerful Apify actor enables you to batch download multiple thumbnails while preserving comprehensive metadata and direct CDN access.** --- ### 📖 Overview Need to analyze Instagram content or gather thumbnails for research? This **Instagram Reels Thumbnail Scraper** delivers: - Multiple thumbnail extraction: Get all available preview images - Apify Storage: Secure download URLs with encryption - Full engagement metrics: Likes, comments, and creator data - Technical metadata: Complete image specifications and codec details Perfect for social media analysts 📊, content researchers 🔍, and app developers 📱! ### ⚡ Core Capabilities/Key Features #### 🖼️ Thumbnail Options - Multiple Thumbnails: Extract all available preview images - High-Quality Images: 640x1136 resolution thumbnails - Bulk Processing: Handle multiple Instagram Reels URLs per run - Direct URLs: Apify storage links for easy access #### 📊 Metadata Mastery - Engagement Analytics: Likes and comments count - Creator Information: Author usernames and profiles - Content Details: Descriptions and upload dates - Technical Specs: Complete image metadata and codec information #### 🔧 Advanced Tech - Proxy Support: Residential IP rotation capabilities - Secure Storage: Encrypted thumbnail URLs - Quality Preservation: Original image quality maintenance --- ### 🎯 Input Configuration Just enter the Instagram Reels URLs in the Input Section then click the "start" button and wait for the results. This **Instagram Reels Thumbnail Scraper** accepts URLs like this: ```json { "reel_urls": [ { "url": "https://www.instagram.com/reel/DKiypWLMTX-/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==", "method": "GET" } ] } ```` #### 📋 Input Specifications | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `reel_urls` | Array | Yes | Instagram Reel URLs to process | | `url` | String | Yes | Valid Instagram Reel URL | | `method` | String | Yes | HTTP method (GET recommended) | *** ### 📄 Output Structure This **Instagram Reels Thumbnail Scraper** provides comprehensive output like this: ```json [ { "original_url": "https://www.instagram.com/reel/DKiypWLMTX-/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==", "author_username": "nba", "description": "TYRESE STRIKES!!.", "likes": "464.6K", "comments": "6.3K", "upload_date": "June 5, 2025", "duration": 12.133, "thumbnail_items_metadata": [ { "url": "https://api.apify.com/v2/key-value-stores/CTC0aHAwJgHLgF9ih/records/thumb_0_6b8b0303-15dc-4bf8-97e9-5dbd18d2d0ef.jpg", "index": 0, "metadata": { "streams": [ { "index": 0, "codec_name": "mjpeg", "codec_long_name": "Motion JPEG", "profile": "Progressive", "codec_type": "video", "width": 640, "height": 1136, "pix_fmt": "yuvj420p", "color_space": "bt470bg" } ], "format": { "format_name": "image2", "format_long_name": "image2 sequence", "duration": "0.040000", "size": "69723", "bit_rate": "13944600" } } } ] } ] ``` #### 📊 Output Field Documentation **Content Metadata Section** | Field | Description | |-------|-------------| | `author_username` | Content creator's Instagram handle | | `description` | Reel description text | | `likes` | Formatted likes count (K/M notation) | | `comments` | Formatted comments count | | `upload_date` | Human-readable publication date | | `duration` | Video length in seconds | **Thumbnail Assets** | Field | Description | |-------|-------------| | `thumbnail_items_metadata` | Array of all available thumbnails | | `url` | Direct thumbnail download URL | | `index` | Thumbnail sequence number | **Technical Image Metadata** | Field | Description | |-------|-------------| | `codec_name` | Image codec (mjpeg, etc.) | | `width` | Image width in pixels | | `height` | Image height in pixels | | `pix_fmt` | Pixel format specification | | `color_space` | Color space information | | `size` | File size in bytes | | `bit_rate` | Bit rate information | *** ### 🎨 Thumbnail Quality & Specifications The **Instagram Reels Thumbnail Scraper** automatically extracts high-quality thumbnails with the following specifications: #### 🖼️ Image Quality - **Resolution**: 640x1136 pixels - **Format**: JPEG with Motion JPEG codec - **Color Space**: BT.470 BG - **Pixel Format**: YUVJ420P progressive #### 🔍 Technical Details - Multiple thumbnail variants per Reel - Complete codec specifications - File size and bit rate metadata - Duration and timing information *** ### 🛠️ Technical Features #### 🖼️ Advanced Image Extraction - Multiple thumbnail capture per Reel - High-resolution image preservation - Motion JPEG codec support - Progressive image formatting #### 📈 Comprehensive Analytics - Engagement metrics extraction - Creator attribution data - Content description capture - Upload timestamp preservation #### 🛡️ Reliability Features - Secure Apify storage integration - Comprehensive error handling - URL validation and normalization - Proxy support for reliable access *** ### 💼 Use Cases - **Social Media Managers** – Analyze competitor thumbnail strategies - **Content Researchers** – Study visual content patterns - **App Developers** – Build thumbnail-powered applications - **Marketing Agencies** – Gather visual intelligence data - **Data Analysts** – Track engagement correlation with thumbnails This **Instagram Reels Thumbnail Scraper** is perfect for anyone needing comprehensive thumbnail data from Instagram Reels content. *** #### 🌟 Why Choose Our Instagram Reels Thumbnail Scraper? - **Reliable Performance**: Stable and efficient thumbnail extraction process - **User-Friendly**: Simple interface for both beginners and advanced users - **Regular Updates**: Maintained to ensure compatibility with Instagram changes - **Comprehensive Data**: Get all thumbnails and metadata in one place - **Secure Access**: Encrypted storage URLs for protected downloads *** #### ⚠️ Limitations - Only works with public Instagram Reels - The **Instagram Reels Thumbnail Scraper** may hit rate limits depending on Instagram's restrictions - Thumbnail availability depends on Instagram's CDN ### 🔗🛠 Related Actors (Full Content Scraping Suite) Explore our full scraping suite for enhanced social media scraping: #### 📸 Instagram Scrapers: - [Instagram Reels Downloader](https://apify.com/codenest/instagram-reels-downloader) - [Instagram Reels Thumbnail Downloader](https://apify.com/codenest/instagram-reels-thumbnail-downloader) - [Instagram Video Downloader](https://apify.com/codenest/instagram-video-downloader) - [Instagram Reels Scraper & Downloader](https://apify.com/codenest/instagram-reels-downloader-scraper) - [Instagram Reels Audio Downloader](https://apify.com/codenest/instagram-reels-audio-downloader) - [Instagram Post Downloader (Image & Video)](https://apify.com/codenest/instagram-post-downloader-image-video) - [Instagram Reels Audio Scraper & Downloader](https://apify.com/codenest/instagram-reels-audio-scraper-downloader) - [Instagram Story Downloader](https://apify.com/codenest/instagram-story-downloader) - [Instagram Story Scraper](https://apify.com/codenest/instagram-story-scraper) *** ### 📧 Need Customization? Want \*higher resolution thumbnails, \*\*batch processing enhancements, or \**additional metadata fields*? ✉ Email ** for tailored solutions with our **Instagram Reels Thumbnail Scraper**! *** # Actor input Schema ## `reel_urls` (type: `array`): A list of public Instagram Reels URLs. Each item can be a string URL or an object with {"url": "https://..."}. ## Actor input object example ```json { "reel_urls": [ { "url": "https://www.instagram.com/reel/DI4WihvBwKC/?utm_source=ig_web_copy_link" } ] } ``` # 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 = { "reel_urls": [ { "url": "https://www.instagram.com/reel/DI4WihvBwKC/?utm_source=ig_web_copy_link" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("codenest/instagram-reels-thumbnail-scraper").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 = { "reel_urls": [{ "url": "https://www.instagram.com/reel/DI4WihvBwKC/?utm_source=ig_web_copy_link" }] } # Run the Actor and wait for it to finish run = client.actor("codenest/instagram-reels-thumbnail-scraper").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 '{ "reel_urls": [ { "url": "https://www.instagram.com/reel/DI4WihvBwKC/?utm_source=ig_web_copy_link" } ] }' | apify call codenest/instagram-reels-thumbnail-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=codenest/instagram-reels-thumbnail-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Reels Thumbnail Scraper", "description": "Extract high-quality thumbnails from Instagram Reels! This scraper delivers multiple preview images with full metadata, engagement stats, and secure Apify KV storage URLs. Perfect for marketers 📈, researchers 🔍, and developers 📱 analysing visual content trends. Instagram Reels Thumbnail Scraper.", "version": "0.0", "x-build-id": "pVlVk5ncbNmjPxKPN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/codenest~instagram-reels-thumbnail-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-codenest-instagram-reels-thumbnail-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/codenest~instagram-reels-thumbnail-scraper/runs": { "post": { "operationId": "runs-sync-codenest-instagram-reels-thumbnail-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/codenest~instagram-reels-thumbnail-scraper/run-sync": { "post": { "operationId": "run-sync-codenest-instagram-reels-thumbnail-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "reel_urls" ], "properties": { "reel_urls": { "title": "Instagram Reels URLs", "type": "array", "description": "A list of public Instagram Reels URLs. Each item can be a string URL or an object with {\"url\": \"https://...\"}.", "items": { "type": "object", "properties": { "url": { "title": "Reels URL", "description": "A list of public Instagram Reels URLs. Each item can be a string URL or an object with {\"url\": \"https://...\"}.", "type": "string", "pattern": "^https://(www\\.)?instagram\\.com/reels?/" } }, "required": [ "url" ] } } } }, "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 } } } } } } } } } } ```