# TikTok Collection Posts Scraper (`powerai/tiktok-collection-posts-scraper`) Actor Export every video from a TikTok playlist into structured rows—captions, creators, and engagement signals ready for reports and dashboards. - **URL**: https://apify.com/powerai/tiktok-collection-posts-scraper.md - **Developed by:** [PowerAI](https://apify.com/powerai) (community) - **Categories:** Social media, Videos, Integrations - **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 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 ## TikTok Collection Posts Scraper Turn a TikTok **playlist or saved collection** into a structured export you can work with in spreadsheets, BI tools, or your own workflows—without manually opening every video. ### Who it’s for - **Brands & creators** who curate official playlists and want a single snapshot of what’s inside, with performance signals in one place. - **Agencies & social teams** tracking campaign or themed collections across clients or regions. - **Growth & content ops** comparing how posts in a collection perform, spotting top performers, and planning what to repost or promote. - **Researchers & analysts** studying themes, languages, and engagement patterns inside a fixed set of videos. ### What you can do with it - **See the full picture** of a collection at a glance: captions, creators, and how each post is performing. - **Back up and archive** a playlist’s contents for reporting, compliance reviews, or internal knowledge bases. - **Support reviews and approvals** when a collection must match brand or campaign guidelines. - **Feed downstream tools**—reports, dashboards, or databases—so marketing and ops don’t copy-paste from the app. ### How it works (in plain terms) You point the tool at one TikTok collection and cap how many videos you want. It walks the list for you and writes **one dataset row per video**, each with a **time stamp** for when that row was exported—handy for “as of” reporting and repeat runs (weekly reviews, campaign wrap-ups). ### Input | Field | Required | What it means | |-------|----------|----------------| | **Collection ID** (`collectionId`) | Yes | The TikTok playlist / collection you want to export. | | **Maximum results** (`maxResults`) | No | Upper limit on how many videos to collect (default **20**, between **20** and **10,000** in the current form). Helps you control cost and run size. | ### Output - **One row per video** in the collection, in export order, until your maximum is reached or the list ends. - Each row carries **what you’d expect for social reporting**: caption text, posting time, creator identity and reach-style signals, and **engagement-style numbers** (for example plays, likes, comments, shares, saves—whatever TikTok surfaces for that post). - **Sound and video context** is included where available (title, length, thumbnails / covers, and similar details you can use in creative or ops reviews). - Every row includes **when that record was written to your dataset**, so stakeholders know which snapshot they’re looking at. - The exact mix of columns can vary slightly by video, account, or region; treat exports as a **best-effort snapshot** of what the platform exposes for that collection. #### Sample output (one dataset row, trimmed) Illustrative shape only: real rows include more fields (e.g. full video and avatar URLs, extra quality variants). Long URL strings are shortened with `…` for readability. ```json { "id": "7459230804909100296", "desc": "Cô giáo Tâm thương thủ trưởng Đại rơi nước mắt #Khongthoigian #VFC #VTV1", "createTime": 1736873100, "playlistId": "7441837327472675591", "author": { "id": "7009062517567013915", "uniqueId": "vfcofficial", "nickname": "VFC Official", "verified": false }, "authorStats": { "followerCount": 614000, "heartCount": 45500000, "videoCount": 1835 }, "stats": { "playCount": 470400, "diggCount": 16700, "commentCount": 63, "shareCount": 54, "collectCount": 421 }, "music": { "id": "7459230886102420225", "title": "original sound - VFC Official", "duration": 88 }, "video": { "id": "7459230804909100296", "duration": 88, "ratio": "540p", "height": 720, "width": 576, "playAddr": "https://v16-webapp-prime.tiktok.com/video/…" }, "textLanguage": "vi", "textTranslatable": true, "scrapedAt": "2026-03-25T02:50:35.665Z" } ```` ### Good to know - TikTok may change how collections look over time; occasional differences between runs are normal. - Use exported information in line with TikTok’s rules and the laws that apply to you and your audience. # Actor input Schema ## `collectionId` (type: `string`): TikTok playlist/collection ID. ## `maxResults` (type: `integer`): Maximum number of posts to collect across pages. ## Actor input object example ```json { "collectionId": "7442134949027351314", "maxResults": 20 } ``` # 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 = { "collectionId": "7442134949027351314", "maxResults": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("powerai/tiktok-collection-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 = { "collectionId": "7442134949027351314", "maxResults": 20, } # Run the Actor and wait for it to finish run = client.actor("powerai/tiktok-collection-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 '{ "collectionId": "7442134949027351314", "maxResults": 20 }' | apify call powerai/tiktok-collection-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=powerai/tiktok-collection-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TikTok Collection Posts Scraper", "description": "Export every video from a TikTok playlist into structured rows—captions, creators, and engagement signals ready for reports and dashboards.", "version": "0.0", "x-build-id": "W393cEuy8H9WO9LUe" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/powerai~tiktok-collection-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-powerai-tiktok-collection-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/powerai~tiktok-collection-posts-scraper/runs": { "post": { "operationId": "runs-sync-powerai-tiktok-collection-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/powerai~tiktok-collection-posts-scraper/run-sync": { "post": { "operationId": "run-sync-powerai-tiktok-collection-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "collectionId" ], "properties": { "collectionId": { "title": "Collection ID", "type": "string", "description": "TikTok playlist/collection ID.", "default": "7442134949027351314" }, "maxResults": { "title": "Maximum Results", "minimum": 20, "maximum": 10000, "type": "integer", "description": "Maximum number of posts to collect across pages.", "default": 20 } } }, "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 } } } } } } } } } } ```