# πŸ”₯ Instagram Scraper(All-in-One) (`easyapi/instagram-scraper`) Actor Extract Instagram posts, reels, comments, profiles, hashtags, and places from any URL or search query. Get structured public data in clean JSON. Try it today! - **URL**: https://apify.com/easyapi/instagram-scraper.md - **Developed by:** [EasyApi](https://apify.com/easyapi) (community) - **Categories:** Social media, Videos - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## πŸ”₯ Instagram Scraper Extract public data from across Instagram in a single tool. Scrape posts, reels, comments, profiles, hashtags, and places using one or more Instagram URLs β€” or discover content by running a search query. Get structured, LLM-ready data in clean JSON. Try it today! ### ✨ Key Features - πŸ“· Scrape **posts and carousels** from profiles, hashtags, or places - 🎞️ Scrape **reels** from profiles, hashtags, or reel pages - πŸ’¬ Scrape **comments and replies** from any post or reel - 🏷️ Scrape **mentions** β€” posts where a profile is tagged - πŸ‘€ Scrape **profile details**: bio, followers, posts count, verified status - #️⃣ Scrape **hashtag details**: post count, related tags, reach tiers - πŸ“ Scrape **place details**: name, coordinates, address, post count - πŸ”Ž **Search** Instagram by hashtag, profile, place, or user - πŸ“… **Filter by date** to get only recent content - πŸ“‹ Clean and structured JSON output, streamed in real time ### πŸ’ͺ Why Choose This Actor? - **Comprehensive**: One tool for posts, reels, comments, profiles, hashtags, and places - **Flexible**: Scrape by URL or discover by search query - **Efficient**: Results are pushed continuously while the job runs - **Structured**: Clean JSON output for easy integration - **Reliable**: Stable and consistent data extraction ### 🎯 Perfect For - πŸ“Š Influencer discovery and vetting - πŸ”₯ Trend tracking and UGC intelligence - 🏒 Competitor and campaign monitoring - πŸ”” Brand monitoring and mentions - πŸ™οΈ Local business discovery and lead generation ### πŸ“ Input Requirements The actor supports two modes β€” **scrape by URL** or **discover by search query**. Pick one mode per run; URLs always take priority if both are filled in. - `contentType` (required): What to extract β€” `posts`, `reels`, `comments`, `mentions`, `details`, or `stories`. Default: `posts` - `targetUrls` (optional): One or more Instagram URLs to scrape (profile, post, reel, hashtag, or place). The URL type must match the content type - `maxResultsPerUrl` (optional): How many posts or comments to scrape per URL. Default: 10 - `postedAfter` (optional): Only return content newer than a date (`YYYY-MM-DD` / ISO) or relative value (e.g. `1 day`, `2 months`, `3 years`). UTC - `searchQuery` (optional): Discover content by keyword instead of URLs. Comma-separate multiple keywords (e.g. `travel, fitness`) - `searchCategory` (optional): What the search returns β€” `hashtag`, `profile`, `place`, or `user`. Default: `hashtag` - `maxSearchResults` (optional): How many profiles, places, or hashtags to find. Default: 10 - `includeSourceLabel` (optional): Adds a `dataSource` field to feed items (`profile` or `hashtag`). Default: false #### Input Example ```json { "contentType": "posts", "targetUrls": [ "https://www.instagram.com/humansofny/" ], "maxResultsPerUrl": 50, "postedAfter": "1 month", "includeSourceLabel": false } ```` #### Output Example ```json { "id": "3742534382104984578", "type": "Sidecar", "shortCode": "DPwJzEVDbwC", "caption": "A few years ago I received a DM from @zohrankmamdani. Only recently did I discover its existence. It was a very unusual DMβ€”especially coming from a local assemblyman who would soon be running for higher office. He had very little name recognition at the time, and could have benefited from publicity. But unlike the thousands of messages I’ve received from people with something to promote, Zohran did not ask to be featured on Humans of New York. Instead he asked if he could introduce me to taxi drivers that were struggling beneath the burden of debt. Coming from a man with political ambitions, this self-denying request was so strange as to be almost singular. I don’t endorse politicians on Humans of New York. But I’ll endorse a good man. And it was a good man who cleared 30 minutes from his schedule yesterday to swing by Grand Central to visit Dear New York. Nearly fifty student artists were visiting that day with their families, and I thought a surprise visit from this widely-loved future mayor would be a special memory for all of them. Before Zohran’s arrival I was convinced I’d made a terrible mistake. The Vanderbilt Hall exhibit was filled to capacity with adult visitors. Dear New York is self-funded so there was very little staff and security for crowd control. In the crush of people I was almost certain this special day for the kids would devolve into thirty minutes of selfie requests. But everyone rose to the occasion. Hundreds of adults quickly cleared the room and stood outside the exhibit. Eleven very notable adult artists are also featured in the exhibition, but even they took a step back, so that these students could briefly have the stage to themselves. Each child stood by their work and Zohran was able to meet all of them, one at a time, and honor their contributions to the most-visited art show in New York City. Thanks to everyone who ceded the stage yesterday to make this moment possible. Thank you Zohran for literally sitting down on the floor so that these young artists could feel so tall. Thank you for continually centering other people in your life and work. And thank you, for being such an important part of Dear New York.", "hashtags": [], "mentions": [ "zohrankmamdani" ], "url": "https://www.instagram.com/p/DPwJzEVDbwC/", "commentsCount": 3961, "firstComment": "I deeply respect this page, but I find this post to be a complete joke.", "latestComments": [ { "id": "18110380114755901", "text": "I deeply respect this page, but I find this post to be a complete joke.", "ownerUsername": "lawandluc", "ownerProfilePicUrl": "https://scontent-ord5-3.cdninstagram.com/v/t51.82787-19/619296377_18559603081010239_1839481113141437498_n.jpg?stp=dst-jpg_s150x150_tt6&_nc_cat=110&ccb=7-5&_nc_sid=f7ccc5&efg=eyJ2ZW5jb2RlX3RhZyI6InByb2ZpbGVfcGljLnd3dy45NjUuQzMifQ%3D%3D&_nc_ohc=_KJctiSTAB0Q7kNvwFKtHG_&_nc_oc=Adp1CYO1t3T85Pg96q0X1fGnr921T0e9k0gS2zSF11gCsg63NLE8N0VpdLiSIViFkU-wmc30gWdVm0UeW7GJzlAC&_nc_zt=24&_nc_ht=scontent-ord5-3.cdninstagram.com&_nc_gid=7rWXmHv9GsboL5ikYhfXPw&_nc_ss=7ca8c&oh=00_AQDRCYsRsH7JzAkb9B0lng9_YyKFPUThq7TwLlFnCJAivQ&oe=6A616CBB", 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"https://scontent-ord5-3.cdninstagram.com/v/t51.82787-19/731014294_18056220689519131_584380576152809831_n.jpg?stp=dst-jpg_s150x150_tt6&_nc_cat=107&ccb=7-5&_nc_sid=f7ccc5&efg=eyJ2ZW5jb2RlX3RhZyI6InByb2ZpbGVfcGljLnd3dy44MTAuQzMifQ%3D%3D&_nc_ohc=tvMhizolKj0Q7kNvwGbIqrO&_nc_oc=Adpec7TAs2YprmxxbL0HACsD5Nia7WnJ4N-QYUJP8HDwai8pe31xElqNdi8souWk1u2mGXNIseTiodAGamgTiSv0&_nc_zt=24&_nc_ht=scontent-ord5-3.cdninstagram.com&_nc_gid=7rWXmHv9GsboL5ikYhfXPw&_nc_ss=7ca8c&oh=00_AQATRBvmFQgB_7sTn3Rgr53JPLXWRKrbyDsZb3wfxtafew&oe=6A6166C0", "timestamp": "2026-07-06T10:11:39.000Z", "repliesCount": null, "replies": null, "likesCount": 0, "owner": { "username": "xcxerryy", "profile_pic_url": 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See the samples in the sections above for the full shape of each type. # Actor input Schema ## `contentType` (type: `string`): What to extract for each Instagram URL or search query. Posts/Reels/Mentions return feed items, Details returns profile/hashtag/place metadata, Comments returns comments from a post or reel. ## `targetUrls` (type: `array`): One or more Instagram URLs to scrape (profile, post, reel, hashtag, or place). URL type must match the content type. Leave blank when using a search query. ## `maxResultsPerUrl` (type: `integer`): How many posts or comments to scrape per Instagram URL. Higher values increase runtime and cost. ## `postedAfter` (type: `string`): Only return content newer than a date (YYYY-MM-DD or ISO) or a relative value (e.g. 1 day, 2 months, 3 years). Times are in UTC. ## `searchQuery` (type: `string`): Discover content by keyword instead of URLs. Comma-separate multiple keywords (e.g. travel, fitness). Enter hashtags as plaintext (travel, not #travel). ## `searchCategory` (type: `string`): What the search query returns: hashtag volume and related tags, matching profiles, matching places, or users. ## `maxSearchResults` (type: `integer`): How many profiles, places, or hashtags to find. Higher values increase runtime and cost. ## `includeSourceLabel` (type: `boolean`): Applies only to feed items. Adds a dataSource field to each result: profile posts are labeled profile, tag posts are labeled hashtag. ## Actor input object example ```json { "contentType": "posts", "targetUrls": [ "https://www.instagram.com/humansofny/" ], "maxResultsPerUrl": 10, "postedAfter": "1 month", "searchCategory": "hashtag", "maxSearchResults": 5, "includeSourceLabel": false } ``` # 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 = { "contentType": "posts", "targetUrls": [ "https://www.instagram.com/humansofny/" ], "maxResultsPerUrl": 10, "postedAfter": "1 month", "searchCategory": "hashtag", "maxSearchResults": 5, "includeSourceLabel": false }; // Run the Actor and wait for it to finish const run = await client.actor("easyapi/instagram-scraper").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 = { "contentType": "posts", "targetUrls": ["https://www.instagram.com/humansofny/"], "maxResultsPerUrl": 10, "postedAfter": "1 month", "searchCategory": "hashtag", "maxSearchResults": 5, "includeSourceLabel": False, } # Run the Actor and wait for it to finish run = client.actor("easyapi/instagram-scraper").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 '{ "contentType": "posts", "targetUrls": [ "https://www.instagram.com/humansofny/" ], "maxResultsPerUrl": 10, "postedAfter": "1 month", "searchCategory": "hashtag", "maxSearchResults": 5, "includeSourceLabel": false }' | apify call easyapi/instagram-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=easyapi/instagram-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "πŸ”₯ Instagram Scraper(All-in-One)", "description": "Extract Instagram posts, reels, comments, profiles, hashtags, and places from any URL or search query. Get structured public data in clean JSON. Try it today!", "version": "0.0", "x-build-id": "vLdspsnbSeYzyk9dW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/easyapi~instagram-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-easyapi-instagram-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/easyapi~instagram-scraper/runs": { "post": { "operationId": "runs-sync-easyapi-instagram-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/easyapi~instagram-scraper/run-sync": { "post": { "operationId": "run-sync-easyapi-instagram-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "contentType" ], "properties": { "contentType": { "title": "Content to scrape", "enum": [ "posts", "reels", "comments", "mentions", "details", "stories" ], "type": "string", "description": "What to extract for each Instagram URL or search query. Posts/Reels/Mentions return feed items, Details returns profile/hashtag/place metadata, Comments returns comments from a post or reel.", "default": "posts" }, "targetUrls": { "title": "Instagram URLs", "type": "array", "description": "One or more Instagram URLs to scrape (profile, post, reel, hashtag, or place). URL type must match the content type. Leave blank when using a search query.", "items": { "type": "string" } }, "maxResultsPerUrl": { "title": "Results limit per URL", "minimum": 1, "type": "integer", "description": "How many posts or comments to scrape per Instagram URL. Higher values increase runtime and cost.", "default": 10 }, "postedAfter": { "title": "Filter by date", "type": "string", "description": "Only return content newer than a date (YYYY-MM-DD or ISO) or a relative value (e.g. 1 day, 2 months, 3 years). Times are in UTC." }, "searchQuery": { "title": "Search query", "type": "string", "description": "Discover content by keyword instead of URLs. Comma-separate multiple keywords (e.g. travel, fitness). Enter hashtags as plaintext (travel, not #travel)." }, "searchCategory": { "title": "Search type", "enum": [ "hashtag", "profile", "place", "user" ], "type": "string", "description": "What the search query returns: hashtag volume and related tags, matching profiles, matching places, or users.", "default": "hashtag" }, "maxSearchResults": { "title": "Search results limit", "minimum": 1, "type": "integer", "description": "How many profiles, places, or hashtags to find. Higher values increase runtime and cost.", "default": 10 }, "includeSourceLabel": { "title": "Add metadata", "type": "boolean", "description": "Applies only to feed items. Adds a dataSource field to each result: profile posts are labeled profile, tag posts are labeled hashtag.", "default": false } } }, "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 } } } } } } } } } } ```