# TikTok Posts Scraper (`scrapesmith/tiktok-posts-scraper`) Actor 🔥$0.25/1000🔥 .Scrape TikTok user profiles at scale. Extract video captions, play counts, likes, shares, comments, hashtags, music, cover images, and posting dates. Bulk scrape multiple profiles with 40,000+ posts per user. Export to JSON, CSV, Excel. No login, no proxies. - **URL**: https://apify.com/scrapesmith/tiktok-posts-scraper.md - **Developed by:** [Scrape Smith](https://apify.com/scrapesmith) (community) - **Categories:** Social media, Other, Videos - **Stats:** 7 total users, 5 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.25 / 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 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 Posts Scraper Scrape all posts from any TikTok profile. Extract video stats, captions, hashtags, music info, engagement data, and more — supports bulk profiles and 40,000+ posts per user. ### What does TikTok Posts Scraper do? This scraper extracts post data from TikTok user profiles. It collects every public post from the profiles you specify, including all engagement metrics. For each post, you get: - **Video** — ID, URL, caption/description, duration, cover image - **Engagement** — play count, likes, comments, shares, saves, reposts - **Metadata** — post date, hashtags, mentions, pinned status, ad flag - **Music** — track title and artist name - **Author** — username, nickname, avatar, verified status For each profile, you also get a summary with follower count, following count, total likes, and video count. ### How much does it cost to run? The scraper runs on just 256 MB RAM. | Posts | Estimated cost | |-------|---------------| | 100 | ~$0.01 | | 1,000 | ~$0.05 | | 10,000 | ~$0.35 | ### Input | Field | Description | Default | |-------|-------------|---------| | **Usernames** | TikTok usernames to scrape (with or without @) | Required | | **Max posts per user** | How many posts to collect per profile. 0 = all posts | 100 | | **Proxy** | Recommended for large runs | Residential | #### Input example ```json { "usernames": ["mrbeast", "charlidamelio"], "maxPosts": 500 } ```` ### Output Each post is stored as a JSON object: ```json { "type": "video", "username": "mrbeast", "videoId": "7388435431126683950", "desc": "Would you eat this? #food", "createTimeISO": "2024-06-28T00:00:00Z", "duration": 42, "playCount": 120000000, "diggCount": 4200000, "commentCount": 32000, "shareCount": 85000, "collectCount": 210000, "videoUrl": "https://www.tiktok.com/@mrbeast/video/7388435431126683950", "authorUniqueId": "mrbeast", "authorNickname": "MrBeast", "authorVerified": true, "musicTitle": "original sound", "hashtags": ["food"], "mentions": [], "isAd": false, "isPinned": false } ``` Each profile also outputs a summary row with follower count, video count, and other profile info. Results can be exported to JSON, CSV, Excel, or accessed via the Apify dataset API. ### Tips - **Start small.** Test with 50-100 posts per user first, then scale up. - **0 = all posts.** Set maxPosts to 0 to scrape every post on a profile. Tested up to 40,000+ posts per user. - **Bulk scraping.** Add as many usernames as you need — the scraper handles them sequentially with automatic resumption. # Actor input Schema ## `usernames` (type: `array`): TikTok usernames to scrape (with or without @ prefix). ## `maxPosts` (type: `integer`): Maximum posts to collect per user. Set to 0 for all posts (40,000+ supported). ## Actor input object example ```json { "usernames": [ "mrbeast" ], "maxPosts": 100 } ``` # 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": [ "mrbeast" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapesmith/tiktok-posts-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": ["mrbeast"] } # Run the Actor and wait for it to finish run = client.actor("scrapesmith/tiktok-posts-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": [ "mrbeast" ] }' | apify call scrapesmith/tiktok-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesmith/tiktok-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TikTok Posts Scraper", "description": "🔥$0.25/1000🔥 .Scrape TikTok user profiles at scale. Extract video captions, play counts, likes, shares, comments, hashtags, music, cover images, and posting dates. Bulk scrape multiple profiles with 40,000+ posts per user. Export to JSON, CSV, Excel. No login, no proxies.", "version": "0.0", "x-build-id": "s1lYFCgp04NAEwwYS" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesmith~tiktok-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesmith-tiktok-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/scrapesmith~tiktok-posts-scraper/runs": { "post": { "operationId": "runs-sync-scrapesmith-tiktok-posts-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/scrapesmith~tiktok-posts-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesmith-tiktok-posts-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", "properties": { "usernames": { "title": "Usernames", "type": "array", "description": "TikTok usernames to scrape (with or without @ prefix).", "items": { "type": "string" } }, "maxPosts": { "title": "Max posts per user", "minimum": 0, "maximum": 100000, "type": "integer", "description": "Maximum posts to collect per user. Set to 0 for all posts (40,000+ supported).", "default": 100 } } }, "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 } } } } } } } } } } ```