# TikTok Following Scraper (No Cookie) (`datadoping/tiktok-following-scraper`) Actor Scrape TikTok following with full profile data. Get usernames, bios, stats, and more. Supports bulk input, pagination, and fast export. Ideal for lead gen, influencer research, and analytics. - **URL**: https://apify.com/datadoping/tiktok-following-scraper.md - **Developed by:** [Data Doping](https://apify.com/datadoping) (community) - **Categories:** Social media, Lead generation - **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.40 / 1,000 followings This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## TikTok Following Scraper TikTok Following Scraper helps you scrape TikTok following lists from public profiles using `uniqueId`, export formats like JSON, CSV, and Excel. If you need a TikTok following scraper for influencer research, competitor intelligence, or lead generation workflows, this actor is optimized for scale and automation. ### Why Use This TikTok Following Scraper - Scrape followings from one or many TikTok profiles in one run. - Export clean, structured data for analytics, BI, and growth teams. ### Typical Use Cases - Competitor following analysis. - Influencer network mapping. - Niche creator discovery. - Ad audience research and enrichment. - Building TikTok social graph datasets. ### Input ```json { "uniqueId": ["taylorswift", "khaby.lame"], "max_count": 120 } ```` #### Input fields - `uniqueId` (array of strings): TikTok usernames/handles to scrape. - `max_count` (integer): maximum followings to collect per `uniqueId`. ### Output Data Each dataset item includes: - The original following payload from provider - Flattened fields for easier filtering and preview: - `following_of` - `following_uid` - `following_unique_id` - `following_nickname` - `avatar_thumb_url` You also get direct profile metrics when present, including: - `favoriting_count` - `follower_count` - `following_count` #### Example output item ```json { "uid": "6881290705605477381", "unique_id": "taylorswift", "nickname": "Taylor Swift", "follower_count": 33461879, "following_count": 0, "favoriting_count": 2292, "following_of": "taylorswift", "following_uid": "6881290705605477381", "following_unique_id": "taylorswift", "following_nickname": "Taylor Swift", "avatar_thumb_url": "https://p16-common-sign.tiktokcdn-us.com/..." } ``` ### FAQ #### Can this scrape private TikTok accounts? No. The actor only returns publicly available data. #### Is this TikTok scraper API-friendly? Yes. It is suitable for scheduled runs, automation pipelines, and downstream API integrations. ### Compliance Note Use this actor only in ways that comply with TikTok terms and your local regulations. # Actor input Schema ## `uniqueId` (type: `array`): List of TikTok uniqueId to scrape. Enter one uniqueId per line. ## `max_count` (type: `integer`): Maximum following to scrape per uniqueId. Default=50 ## Actor input object example ```json { "uniqueId": [ "heart.robber3" ], "max_count": 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 = { "uniqueId": [ "heart.robber3" ], "max_count": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("datadoping/tiktok-following-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 = { "uniqueId": ["heart.robber3"], "max_count": 50, } # Run the Actor and wait for it to finish run = client.actor("datadoping/tiktok-following-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 '{ "uniqueId": [ "heart.robber3" ], "max_count": 50 }' | apify call datadoping/tiktok-following-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datadoping/tiktok-following-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TikTok Following Scraper (No Cookie)", "description": "Scrape TikTok following with full profile data. Get usernames, bios, stats, and more. Supports bulk input, pagination, and fast export. Ideal for lead gen, influencer research, and analytics.", "version": "0.0", "x-build-id": "Y0HB6YtfdaGNKboZL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datadoping~tiktok-following-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datadoping-tiktok-following-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datadoping~tiktok-following-scraper/runs": { "post": { "operationId": "runs-sync-datadoping-tiktok-following-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datadoping~tiktok-following-scraper/run-sync": { "post": { "operationId": "run-sync-datadoping-tiktok-following-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "uniqueId", "max_count" ], "properties": { "uniqueId": { "title": "TikTok Unique ID", "type": "array", "description": "List of TikTok uniqueId to scrape. Enter one uniqueId per line.", "items": { "type": "string" } }, "max_count": { "title": "Max Following", "minimum": 50, "type": "integer", "description": "Maximum following to scrape per uniqueId. 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 } } } } } } } } } } ```