# Threads User Followers Scraper (`apibox/threads-user-followers-scraper`) Actor Extract User Followers from Threads, including id, username, follower count and verified. Easily collect and analyze user-generated content, and download results in formats like JSON, CSV, or Excel. - **URL**: https://apify.com/apibox/threads-user-followers-scraper.md - **Developed by:** [ApiBox](https://apify.com/apibox) (community) - **Categories:** Social media - **Stats:** 73 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $19.00/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 ### Threads User Follower Scraper #### πŸ“– What is Threads? Threads is a social messaging platform focused on fostering authentic conversations. Users can post and share text, images and videos to join in public discussions. Threads was developed by Meta’s Instagram team and launched on July 5, 2023. [πŸ”—](https://sproutsocial.com/insights/meta-threads/) #### ❓ What is Threads User Follower Scraper? Threads User Follower Scraper is a data extraction tool created for scraping follower of user from Threads. #### ⚑ How do I use Threads User Follower Scraper? 1. Create an [Apify](https://www.apify.com?fpr=hs6s8) account 2. Open [Threads User Follower Scraper](https://apify.com/apibox/threads-user-followers-scraper?fpr=hs6s8) 3. Add Input parameters 4. Click the β€œStart” button and wait for the data to be extracted. Download your data in JSON, XML, CSV, Excel, or HTML #### ⬇️ Input parameters The input of this scraper should be JSON containing the list of pages that should be visited. Check the input tab for detailed list. ##### Input Example ```json { "username": "zuck", "num": 50 } ```` #### ⬆️ Output You can download the resulting dataset in various formats such as JSON, HTML, CSV or Excel. The structure of each post detail looks like this: ##### Output Examplee ```json { "id": "12281817", "profile_pic_url": "https://instagram.fmaa10-1.fna.fbcdn.net/v/t51.2885-19/430869627_1109934706918340_7402884675761038685_n.jpg?stp=dst-jpg_s150x150&_nc_ht=instagram.fmaa10-1.fna.fbcdn.net&_nc_cat=108&_nc_ohc=cYaaaIb9XJMQ7kNvgGs9FcG&edm=APs17CUBAAAA&ccb=7-5&oh=00_AYBjuBzlAglvGGpwIfKQfdGJicziL3ZvDGauVxbLqzlDJA&oe=66B78D98&_nc_sid=10d13b", "username": "kyliejenner", "full_name": "Kylie", "follower_count": 14598837, "is_verified": true } ``` #### πŸ”— Integrations You can use [Make](https://www.make.com/en/register?pc=apibox) to integrate this scraper to any other SaaS platform by designing your own automation flows. #### πŸ“ˆ Other Threads Scraper
πŸ’¬ Threads User Post Scraper πŸ“œ Threads Post Activity Scraper
🐻 Threads User Following Scraper πŸ’¬ Threads User Reply Scraper
#### πŸ“¬ Contact We value your feedback and are here to assist you with any questions or concerns you may have. Feel free to reach out to us through the following email apiboxguru@gmail.com # Actor input Schema ## `username` (type: `string`): The username you want to get the data from ## `num` (type: `integer`): Maximum number of followers that you want to scrape ## Actor input object example ```json { "username": "askmeknowledge", "num": 50 } ``` # 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": "askmeknowledge" }; // Run the Actor and wait for it to finish const run = await client.actor("apibox/threads-user-followers-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 = { "username": "askmeknowledge" } # Run the Actor and wait for it to finish run = client.actor("apibox/threads-user-followers-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 '{ "username": "askmeknowledge" }' | apify call apibox/threads-user-followers-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=apibox/threads-user-followers-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Threads User Followers Scraper", "description": "Extract User Followers from Threads, including id, username, follower count and verified. Easily collect and analyze user-generated content, and download results in formats like JSON, CSV, or Excel.", "version": "0.0", "x-build-id": "ebw2fDvvxMl5FkuNt" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/apibox~threads-user-followers-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-apibox-threads-user-followers-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/apibox~threads-user-followers-scraper/runs": { "post": { "operationId": "runs-sync-apibox-threads-user-followers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/apibox~threads-user-followers-scraper/run-sync": { "post": { "operationId": "run-sync-apibox-threads-user-followers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "string", "description": "The username you want to get the data from" }, "num": { "title": "Number of followers", "type": "integer", "description": "Maximum number of followers that you want to scrape", "default": 50 } } }, "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 } } } } } } } } } } ```