# Instagram Post & Profile Scraper (`sophisticated_zythum/instagram-post-profile-scraper`) Actor Extract Instagram profile data including followers, posts count, engagement metrics, hashtags and content details. Perfect for competitor analysis, influencer research and market insights. Uses Bright Data's Instagram Scraper API for reliable data extraction. - **URL**: https://apify.com/sophisticated\_zythum/instagram-post-profile-scraper.md - **Developed by:** [Md Saif Ahmed](https://apify.com/sophisticated_zythum) (community) - **Categories:** Social media, Agents, SEO tools - **Stats:** 4 total users, 3 monthly users, 94.1% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 per profiles This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Instagram Post & Profile Scraper Extract Instagram profile data, posts, engagement metrics, and hashtags from any public Instagram account. ### What it does For each username you provide, the actor collects: - **Profile** — followers, following, bio, verified status, business category, engagement rate - **Posts** — images, videos, carousels, and reels with likes, comments, captions, and media URLs - **Hashtags** — aggregated list of all hashtags used across posts ### Input | Field | Type | Default | Description | |---|---|---|---| | `usernames` | string[] | — | Instagram usernames to scrape (required) | | `maxPosts` | integer | 20 | Max posts to collect per profile (5–500) | | `minLikes` | integer | 0 | Skip posts with fewer likes than this | | `scrapeReels` | boolean | true | Include reels in results | | `startDate` | string | — | Only posts on or after this date (`YYYY-MM-DD`) | | `endDate` | string | — | Only posts on or before this date (`YYYY-MM-DD`) | | `newerThan` | integer | — | Only posts from the last N days | #### Example input ```json { "usernames": ["natgeo", "nasa"], "maxPosts": 20, "minLikes": 100, "scrapeReels": true, "newerThan": 30 } ```` ### Output The dataset contains three record types per profile: #### Profile record ```json { "type": "profile", "username": "natgeo", "fullName": "National Geographic", "followers": 271054801, "following": 165, "bio": "...", "isVerified": true, "isBusiness": true, "category": "Media/news company", "avgEngagement": 0.43, "extractedAt": "2026-05-07T10:00:00.000Z" } ``` #### Post record ```json { "type": "post", "username": "natgeo", "postId": "abc123", "contentType": "Image", "caption": "...", "likes": 45231, "comments": 312, "postUrl": "https://www.instagram.com/p/abc123", "mediaUrl": "https://...", "timestamp": "2026-04-15T12:00:00.000Z", "hashtags": ["#nature", "#wildlife"], "extractedAt": "2026-05-07T10:00:00.000Z" } ``` #### Hashtags record ```json { "type": "hashtags", "username": "natgeo", "hashtags": ["#nature", "#wildlife", "#photography"], "count": 3, "extractedAt": "2026-05-07T10:00:00.000Z" } ``` ### Pricing This actor uses pay-per-record pricing at **$2.99 per 1,000 records**. A record is either a profile or a post. For example: - 1 username × 20 posts = **21 records = ~$0.06** - 10 usernames × 20 posts = **210 records = ~$0.63** # Actor input Schema ## `usernames` (type: `array`): Instagram usernames to extract ## `maxPosts` (type: `integer`): Maximum posts to collect per profile (minimum 5) ## `minLikes` (type: `integer`): Skip posts with fewer likes than this ## `includeImages` (type: `boolean`): Include image posts in results ## `includeVideos` (type: `boolean`): Include video posts in results ## `includeCarousels` (type: `boolean`): Include carousel posts in results ## `includeReels` (type: `boolean`): Include reels in results ## `startDate` (type: `string`): Only include posts on or after this date (YYYY-MM-DD) ## `endDate` (type: `string`): Only include posts on or before this date (YYYY-MM-DD) ## `newerThan` (type: `integer`): Only include posts from the last N days ## Actor input object example ```json { "usernames": [ "mamaearth.in" ], "maxPosts": 20, "minLikes": 0, "includeImages": true, "includeVideos": true, "includeCarousels": true, "includeReels": true } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "usernames": [ "mamaearth.in" ] }; // Run the Actor and wait for it to finish const run = await client.actor("sophisticated_zythum/instagram-post-profile-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "usernames": ["mamaearth.in"] } # Run the Actor and wait for it to finish run = client.actor("sophisticated_zythum/instagram-post-profile-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 '{ "usernames": [ "mamaearth.in" ] }' | apify call sophisticated_zythum/instagram-post-profile-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=sophisticated_zythum/instagram-post-profile-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Post & Profile Scraper", "description": "Extract Instagram profile data including followers, posts count, engagement metrics, hashtags and content details. Perfect for competitor analysis, influencer research and market insights. Uses Bright Data's Instagram Scraper API for reliable data extraction.", "version": "0.0", "x-build-id": "xEAcAnWwMa4K9fHl5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/sophisticated_zythum~instagram-post-profile-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-sophisticated_zythum-instagram-post-profile-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/sophisticated_zythum~instagram-post-profile-scraper/runs": { "post": { "operationId": "runs-sync-sophisticated_zythum-instagram-post-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/sophisticated_zythum~instagram-post-profile-scraper/run-sync": { "post": { "operationId": "run-sync-sophisticated_zythum-instagram-post-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "usernames" ], "properties": { "usernames": { "title": "Usernames", "type": "array", "description": "Instagram usernames to extract", "items": { "type": "string" } }, "maxPosts": { "title": "Max Posts", "minimum": 5, "maximum": 500, "type": "integer", "description": "Maximum posts to collect per profile (minimum 5)", "default": 20 }, "minLikes": { "title": "Minimum Likes", "type": "integer", "description": "Skip posts with fewer likes than this", "default": 0 }, "includeImages": { "title": "Include Images", "type": "boolean", "description": "Include image posts in results", "default": true }, "includeVideos": { "title": "Include Videos", "type": "boolean", "description": "Include video posts in results", "default": true }, "includeCarousels": { "title": "Include Carousels", "type": "boolean", "description": "Include carousel posts in results", "default": true }, "includeReels": { "title": "Include Reels", "type": "boolean", "description": "Include reels in results", "default": true }, "startDate": { "title": "Start Date", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Only include posts on or after this date (YYYY-MM-DD)" }, "endDate": { "title": "End Date", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Only include posts on or before this date (YYYY-MM-DD)" }, "newerThan": { "title": "Newer Than (days)", "type": "integer", "description": "Only include posts from the last N days" } } }, "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 } } } } } } } } } } ```