# TikTok Ads Library Scraper (`prodiger/tiktok-ads-library-scraper`) Actor Scrape TikTok's Ad Library by keyword, advertiser name, or business ID across supported regions. - **URL**: https://apify.com/prodiger/tiktok-ads-library-scraper.md - **Developed by:** [Arnas](https://apify.com/prodiger) (community) - **Categories:** Agents, Automation, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $3.00 / 1,000 ad scrapeds 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 Ads Library Scraper Scrape TikTok's official Ads Library by keyword, advertiser name, or advertiser business ID across supported regions. The Actor returns clean JSON with ad IDs, advertiser names, ad type, first/last shown dates, estimated audience, spend buckets, media URLs, cover images, rejection info when TikTok discloses it, and a TikTok Ads Library deeplink. ### Input At least one of `search`, `ad_id`, or `adv_biz_ids` is required. | Field | Default | Description | | --- | --- | --- | | `search` | - | Advertiser name or keyword. | | `ad_id` | - | Specific ad ID. When used alone, returns a deeplink record. | | `adv_biz_ids` | - | TikTok advertiser business ID. | | `region` | `all` | ISO country code or `all`. TikTok does not support `US`; use `all` for global results. | | `query_type` | `1` | `1` = advertiser name, `0` = keyword. | | `sort` | `last_shown_date,desc` | Sort by shown dates or impressions. | | `start_date` | one year ago | Lower bound for last-shown date, `YYYY-MM-DD`. | | `end_date` | today | Upper bound for last-shown date, `YYYY-MM-DD`. | | `limit` | `20` | Number of ads to return, 1-100. | | `offset` | `0` | TikTok page offset. | | `search_id` | - | Optional pagination token returned by TikTok. | | `proxy_url` | - | Optional HTTP(S) proxy URL. | ### Output Each dataset item has `type: "ad"` for search results or `type: "ad-deeplink"` for ad-ID-only runs. Important fields: - `adId`, `advertiserName`, `auditStatus`, `adType` - `firstShownAt`, `lastShownAt`, `daysRunning` - `estimatedAudience`, `spend`, `impressions` - `videoUrls`, `coverImageUrls`, `imageUrls` - `rejectionInfo`, `deeplink` The run `OUTPUT` includes `total`, `pushed`, `hasMore`, `searchId`, and `nextOffset` for pagination. To fetch the next page, pass both `offset: nextOffset` and `search_id: searchId` from the previous run — the TikTok cursor is required for pages beyond the first. # Actor input Schema ## `search` (type: `string`): Advertiser name or keyword, for example nike or korean skincare. One of search, ad_id, or adv_biz_ids is required. ## `ad_id` (type: `string`): Specific ad ID. Returns the TikTok Ads Library deeplink when used without search or adv_biz_ids. ## `adv_biz_ids` (type: `string`): TikTok advertiser business ID filter. ## `region` (type: `string`): ISO country code or all. TikTok Ad Library does not support region=US; use all to include US ads in global results. ## `query_type` (type: `string`): 1 = search by advertiser name, 0 = search by keyword. ## `sort` (type: `string`): Order results by recency or impression count. ## `start_date` (type: `string`): Lower bound for last-shown date as YYYY-MM-DD. Defaults to one year ago. ## `end_date` (type: `string`): Upper bound for last-shown date as YYYY-MM-DD. Defaults to today. ## `limit` (type: `integer`): Max ads per request. ## `offset` (type: `integer`): TikTok page offset. Use nextOffset from OUTPUT for the next page. ## `search_id` (type: `string`): Optional TikTok search_id from a previous page. Usually leave empty for the first request. ## `proxy_url` (type: `string`): Optional IPv4 HTTP(S) proxy URL in the form scheme://username:password@host:port. ## Actor input object example ```json { "search": "nike", "region": "all", "query_type": "1", "sort": "last_shown_date,desc", "limit": 20, "offset": 0 } ```` # 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 = { "search": "nike" }; // Run the Actor and wait for it to finish const run = await client.actor("prodiger/tiktok-ads-library-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 = { "search": "nike" } # Run the Actor and wait for it to finish run = client.actor("prodiger/tiktok-ads-library-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 '{ "search": "nike" }' | apify call prodiger/tiktok-ads-library-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=prodiger/tiktok-ads-library-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TikTok Ads Library Scraper", "description": "Scrape TikTok's Ad Library by keyword, advertiser name, or business ID across supported regions.", "version": "0.1", "x-build-id": "bWmZZQfzd78KvvsaI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/prodiger~tiktok-ads-library-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-prodiger-tiktok-ads-library-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/prodiger~tiktok-ads-library-scraper/runs": { "post": { "operationId": "runs-sync-prodiger-tiktok-ads-library-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/prodiger~tiktok-ads-library-scraper/run-sync": { "post": { "operationId": "run-sync-prodiger-tiktok-ads-library-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "search": { "title": "Search query", "type": "string", "description": "Advertiser name or keyword, for example nike or korean skincare. One of search, ad_id, or adv_biz_ids is required." }, "ad_id": { "title": "Ad ID", "type": "string", "description": "Specific ad ID. Returns the TikTok Ads Library deeplink when used without search or adv_biz_ids." }, "adv_biz_ids": { "title": "Advertiser business ID", "type": "string", "description": "TikTok advertiser business ID filter." }, "region": { "title": "Region", "enum": [ "all", "NL", "DE", "BE", "FR", "GB", "ES", "IT", "AT", "CH", "PL", "SE", "DK", "NO", "FI", "PT", "IE", "AU", "CA", "NZ", "JP", "KR", "BR", "MX", "IN", "TR", "ZA", "AR", "CL", "CO", "EG", "SA", "AE", "IL", "SG", "MY", "TH", "PH", "ID", "VN", "TW", "HK" ], "type": "string", "description": "ISO country code or all. TikTok Ad Library does not support region=US; use all to include US ads in global results.", "default": "all" }, "query_type": { "title": "Query type", "enum": [ "1", "0" ], "type": "string", "description": "1 = search by advertiser name, 0 = search by keyword.", "default": "1" }, "sort": { "title": "Sort order", "enum": [ "last_shown_date,desc", "last_shown_date,asc", "first_shown_date,desc", "first_shown_date,asc", "impression,desc", "impression,asc" ], "type": "string", "description": "Order results by recency or impression count.", "default": "last_shown_date,desc" }, "start_date": { "title": "Start date", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Lower bound for last-shown date as YYYY-MM-DD. Defaults to one year ago." }, "end_date": { "title": "End date", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Upper bound for last-shown date as YYYY-MM-DD. Defaults to today." }, "limit": { "title": "Number of ads", "minimum": 1, "maximum": 100, "type": "integer", "description": "Max ads per request.", "default": 20 }, "offset": { "title": "Pagination offset", "minimum": 0, "type": "integer", "description": "TikTok page offset. Use nextOffset from OUTPUT for the next page.", "default": 0 }, "search_id": { "title": "Search ID", "type": "string", "description": "Optional TikTok search_id from a previous page. Usually leave empty for the first request." }, "proxy_url": { "title": "Proxy URL (optional, advanced)", "type": "string", "description": "Optional IPv4 HTTP(S) proxy URL in the form scheme://username:password@host:port." } } }, "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 } } } } } } } } } } ```