# Instagram Followers Count Scraper (Profile) (`scrapecraze/instagram-followers-count-scraper`) Actor Instagram Followers Count Scraper extracts publicly available follower count data from Instagram profiles at scale. Collect usernames, follower numbers, following counts, bio data, and profile metrics for audience analysis, influencer research, competitor tracking, and social media insights. - **URL**: https://apify.com/scrapecraze/instagram-followers-count-scraper.md - **Developed by:** [ScrapeCraze](https://apify.com/scrapecraze) (community) - **Categories:** Social media, Lead generation, Automation - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 results 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 Followers Count Scraper 🚀 — Get follower counts from Instagram profiles in bulk Instagram follower counts are scattered across profile pages, and manually checking them doesn’t scale when you’re building lists for outreach or reporting. **Instagram Followers Count Scraper** pulls follower and following counts for the Instagram usernames you provide, so you can turn public web data into structured results fast. This Instagram followers count scraper (and IG followers count scraper) is built for marketers, analysts, and researchers who need follower count data extraction without repetitive copy-pasting. It’s ideal when you need Instagram profile scraper followers data for multiple accounts in a single run—typically starting to appear within seconds. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "profilePic": "https://example.com/profile_pic_hd.jpg", "userName": "mrbeast", "followersCount": 100000000, "followsCount": 200, "timestamp": "2026-06-07 - 14:32", "userUrl": "https://www.instagram.com/mrbeast", "userFullName": "MrBeast", "userId": 1234567890, "biography": "🎥 Creator | Business inquiries via link in bio", "externalUrl": "https://example.com" } ```` | Field | Type | What It Tells You | |---|---|---| | profilePic | string | Lets you quickly visually verify the profile while reviewing results. | | userName | string | The Instagram handle used to fetch the record (useful as your join key). | | followersCount | number | The follower count at the time the actor scraped the profile. | | followsCount | number | The “following” count shown for the profile. | | timestamp | string | A capture timestamp (formatted as `YYYY-MM-DD - HH:MM`) so you can track changes over time. | | userUrl | string | Direct link to the Instagram profile for quick auditing and sharing internally. | | userFullName | string | The public display name for easier human review. | | userId | number | The profile’s numeric ID for stable identification across systems. | | biography | string | Public bio text you can use for filtering or context in analyses. | | externalUrl | string | The external link set on the profile (often useful for routing or segmentation). | | status | string | This actor pushes profile objects to the dataset; if a profile fails, it is logged and not included as a dataset row (see limitations below). | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "username": [ "mrbeast", "cristiano" ] } ``` | Parameter | Required | What It Does | |---|---|---| | `username` | ✅ | Provide a list of Instagram usernames whose followers count you want to extract. | *** ### What It Does The **Instagram Followers Count Scraper** retrieves follower metrics and related profile metadata for each Instagram username you supply, then writes the results to your dataset. #### Scrape follower and following counts for each username For every handle in your `username` list, it extracts `followersCount` (followers) and `followsCount` (following) alongside useful profile context like `userFullName` and `biography`. #### Built for Instagram followers count scraper workflows Whether you’re building a creator shortlist, monitoring Instagram follower count trends, or comparing cohorts, the actor outputs structured fields you can join with other datasets (e.g., campaign records or scoring sheets). #### Consistent, integration-friendly dataset fields Each successful profile scrape is pushed as a dataset row containing `profilePic`, `userUrl`, `userId`, `externalUrl`, and a `timestamp` so your downstream processing stays reliable. #### Includes resilience for public profile requests The actor uses built-in retries and fallback behavior when requests fail or a profile can’t be fetched (e.g., profiles not found are handled as `None` internally and not pushed). #### Private account access isn’t part of the scope This is an Instagram profile scraper followers tool designed for publicly accessible profile data. You’ll get results for profiles the actor can retrieve, and missing or inaccessible profiles won’t appear as dataset rows. Overall, **Instagram Followers Count Scraper** turns public Instagram profile data into clean follower count data extraction you can use immediately. *** ### Why Instagram Followers Count Scraper? There are plenty of ways to pull data from Instagram — here’s why **Instagram Followers Count Scraper** stands out. #### Structured output that’s ready for analysis Instead of leaving you with messy page text, the actor outputs consistent JSON fields like `followersCount`, `followsCount`, and `timestamp`, which makes Instagram follower statistics scraper workflows smoother. #### Reliability-focused run behavior The actor includes retries and handles non-success cases without crashing the entire run, so batch jobs can still produce useful output even when some usernames don’t resolve. #### Built for bulk lists, not one-off checks If your goal is scrape IG followers number across many accounts, this actor processes the `username` array end-to-end and pushes results into the dataset in one run. *** ### Real-World Use Cases **Influencer marketing teams** often need to shortlist creators quickly. They can feed a list of Instagram handles into **Instagram Followers Count Scraper**, instantly generate follower count analytics scraper results, and move straight into outreach targeting based on follower thresholds. **Sales and partnerships researchers** use Instagram follower count data extraction when they need to quantify potential leads. By collecting `followersCount`, `followsCount`, and `externalUrl` in one dataset, they can prioritize accounts that match campaign fit before they ever open a profile manually. **Brand analysts tracking growth** want comparable snapshots over time. With the `timestamp` field included per record, they can rerun the actor on the same usernames and spot changes for Instagram growth tracking scraper reporting. **Automation specialists and data engineers** integrate this output into pipelines. After the run, they can export the dataset and feed follower count monitoring tool workflows (e.g., scoring models or dashboards) without reformatting. **Freelance researchers** often juggle multiple client spreadsheets. This Instagram followers count checker approach helps them deliver consistent follower count data alongside `userId` and `userUrl`, reducing cleanup time between sources. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Open the actor on Apify**\ Go to the actor page on [console.apify.com](https://console.apify.com). 2. **Enter your inputs**\ Add an array of handles to the `username` field (the list of Instagram usernames to extract followers count from). 3. **Use proxy support (recommended)**\ Configure proxy settings for more reliable scraping, especially when processing larger username lists. 4. **Start the run and watch the live log**\ Monitor progress in the Apify console; you’ll see which usernames are being fetched. 5. **Open the Dataset tab to see live results**\ Each successfully scraped profile appears with fields like `followersCount`, `userUrl`, and `timestamp`. 6. **Export in your preferred format**\ Download your dataset from the dashboard as JSON, CSV, or Excel. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, **Instagram Followers Count Scraper** fits directly into your existing workflow. You can download results from the Apify dataset tab in common formats like JSON, CSV, or Excel for use in reporting and spreadsheet-based analysis. For no-code automations, you can connect dataset exports to tools like Zapier or Make using Apify’s integration capabilities. If you’re building a pipeline, you can also pull results programmatically via the Apify API and wire it into your own storage, dashboards, or scheduled processes. Webhooks and scheduled runs can trigger downstream actions when a job completes. *** ### Pricing Instagram Followers Count Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. On Apify, usage typically runs on a free allowance first (platform credits for testing). For heavier workloads, you’ll scale using Apify’s pay-as-you-go compute model and subscription plans available on the pricing page. Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Rate-limit style failures | Uses retry logic with back-off behavior. | | Missing/invalid profiles | Profiles that can’t be retrieved (for example, not found) are handled without stopping the run. | | Batch robustness | Continues processing other usernames even if one fails. | | Output consistency | Successful results are pushed to the dataset with the same fields. | Limitations: This actor is designed for publicly accessible Instagram profiles. Login-gated or private profile pages are out of scope, and any usernames that can’t be fetched won’t appear as dataset rows. For enterprise-scale needs or custom configurations, reach out and we'll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes—Apify provides a free tier with platform credits so you can run small tests before scaling up. #### Do I need to log in or create an account on Instagram? No. This actor is designed to scrape follower counts from publicly available profile data using the usernames you provide, without requiring an Instagram login. #### How accurate is the extracted data? The actor extracts the follower and following counts and related profile fields from publicly accessible sources. Accuracy depends on what’s shown on the profile at the time of the scrape. #### How many results can I get per run? You can include multiple usernames in the `username` array and the actor processes them in a single run. The practical number of results depends on your Apify run limits and plan. #### How fresh is the data? The `timestamp` field is generated at scrape time, so the follower counts reflect the moment the actor retrieved the profile information. #### Is this legal? Does it comply with GDPR / CCPA? The actor works with **publicly available data**. It’s your responsibility to comply with GDPR, CCPA, Instagram’s Terms of Service, and any applicable laws when collecting, storing, or using the data. #### Can I export to Google Sheets or Excel? Yes. You can export your dataset from the Apify dashboard (JSON, CSV, or Excel). From there, you can import into Excel directly or connect to Google Sheets via your usual workflow. #### Can I schedule this to run automatically? Yes. On Apify, you can set up scheduled runs so the actor executes automatically on a recurring schedule. #### Can I access results via the API? Yes. After the run, you can access dataset results using Apify’s API capabilities. #### What happens when the actor encounters an error? Errors for specific usernames are logged, and the run continues. Only successfully scraped profiles are pushed to the dataset. *** ### Get Help & Use Responsibly Got a question about Instagram Followers Count Scraper or a feature you'd like added? Reach out at . We welcome requests and actively maintain this actor based on community feedback, including ideas like additional profile fields in the output and better run-time filtering. *** **This actor collects data only from publicly available data.** It does not access private accounts, login-gated pages, or password-protected content. You’re responsible for complying with GDPR, CCPA, and platform Terms of Service when using or storing the results. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `username` (type: `array`): The username(s) to extract followers count. ## Actor input object example ```json { "username": [ "mrbeast" ] } ``` # 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 = { "username": [ "mrbeast" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapecraze/instagram-followers-count-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 = { "username": ["mrbeast"] } # Run the Actor and wait for it to finish run = client.actor("scrapecraze/instagram-followers-count-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 '{ "username": [ "mrbeast" ] }' | apify call scrapecraze/instagram-followers-count-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapecraze/instagram-followers-count-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Followers Count Scraper (Profile)", "description": "Instagram Followers Count Scraper extracts publicly available follower count data from Instagram profiles at scale. Collect usernames, follower numbers, following counts, bio data, and profile metrics for audience analysis, influencer research, competitor tracking, and social media insights.", "version": "1.0", "x-build-id": "JU3KRCqgVG3vIgqgn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapecraze~instagram-followers-count-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapecraze-instagram-followers-count-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapecraze~instagram-followers-count-scraper/runs": { "post": { "operationId": "runs-sync-scrapecraze-instagram-followers-count-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapecraze~instagram-followers-count-scraper/run-sync": { "post": { "operationId": "run-sync-scrapecraze-instagram-followers-count-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "username" ], "properties": { "username": { "title": "Username", "type": "array", "description": "The username(s) to extract followers count.", "default": [ "mrbeast" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```