# TikTok Comments Scraper ⚡ (`forlex/tiktok-comments-scraper`) Actor Lightning-fast scraper to extract TikTok comments, nested replies, likes, and user data. Includes date filtering and sorting. - **URL**: https://apify.com/forlex/tiktok-comments-scraper.md - **Developed by:** [Forlex Lab](https://apify.com/forlex) (community) - **Categories:** Social media, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.45 / 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. 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 Comments Scraper (Ultra-Fast) The most advanced, fastest, and most cost-effective TikTok Comments Scraper on the Apify Store. Extract thousands of comments and nested replies in seconds, completely bypassing heavy, slow browsers. Whether you are a marketing agency doing sentiment analysis, a brand looking for lead generation, or a researcher analyzing viral trends, this tool is built for you. ### ✨ Key Features - ⚡ **Lightning Fast:** Extracts up to 1,000 comments in under 2 seconds. - 🎯 **Deep Reply Scraping:** Automatically dive into comment threads and extract nested replies. - 📅 **Date Filtering:** Only want comments from a specific date range? Use our native calendar widget to filter exactly what you need. - ❤️ **Quality Filtering:** Set a `Min Likes` or `Min Replies` threshold to automatically filter out spam and only extract the most highly-engaged comments. - 📊 **Smart Sorting:** Sort your final dataset by `Most Liked`, `Most Recent`, `Most Replied`, or TikTok's default `Top` algorithm. - 🛡️ **Bulletproof Anti-Bot:** Native integration with Apify's Residential and Datacenter Proxies ensures your scraper never gets blocked. ### 📥 Input Configuration We have designed a beautifully organized, premium UI for ease of use. 1. **⚙️ Extraction Settings:** Paste your TikTok Video URLs and set the maximum number of comments and replies you want to extract. 2. **🔍 Filters:** Set your date ranges and minimum engagement metrics. 3. **🌐 Proxy Configuration:** Leave on "Automatic" to utilize Apify's proxy pool for maximum stability. ### 📤 Output Structure The scraper delivers exceptionally clean, structured JSON/CSV data ready for analysis. You will receive: - `video_url` - `text` (The comment) - `likes` & `replies_count` - `date_posted` & `create_time` - `user_username`, `user_nickname`, `user_id` (Perfect for profile lead generation!) - `is_reply` ### 💡 Use Cases - **Sentiment Analysis:** Export highly-liked comments to ChatGPT/Claude to analyze public perception of a brand or product. - **Lead Generation:** Extract the usernames of people asking "Where can I buy this?" and target them. - **Competitor Research:** Analyze what your competitors' audience is saying in their comment sections. --- *Note: Due to TikTok's platform protections, scraping more than 1,000-2,000 top-level comments per video may require advanced residential proxies. Our deep-reply scraping feature is the best way to uncover hidden comments beyond standard limits.* # Actor input Schema ## `postURLs` (type: `array`): URLs of TikTok videos ## `maxComments` (type: `integer`): Maximum number of comments to extract. ## `maxRepliesPerComment` (type: `integer`): Maximum number of nested replies to extract per top-level comment. Set to 0 to ignore replies. ## `sortBy` (type: `string`): How to sort the final extracted comments. ## `dateFrom` (type: `string`): Optional: Only extract comments posted on or after this date (e.g. 2024-01-01). ## `dateTo` (type: `string`): Optional: Only extract comments posted on or before this date (e.g. 2024-12-31). ## `minLikes` (type: `integer`): Optional: Only extract comments with at least this many likes. ## `minReplies` (type: `integer`): Optional: Only extract comments with at least this many replies. ## `proxyConfiguration` (type: `object`): Select proxies to be used. Residential proxies are highly recommended to avoid TikTok's anti-bot measures. ## Actor input object example ```json { "postURLs": [ "https://www.tiktok.com/@tiktok/video/7106594312292453675" ], "maxComments": 100, "maxRepliesPerComment": 0, "sortBy": "Top", "minLikes": 0, "minReplies": 0, "proxyConfiguration": { "useApifyProxy": true } } ```` # Actor output Schema ## `dataset` (type: `string`): No description # 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 = { "postURLs": [ "https://www.tiktok.com/@tiktok/video/7106594312292453675" ], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("forlex/tiktok-comments-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 = { "postURLs": ["https://www.tiktok.com/@tiktok/video/7106594312292453675"], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("forlex/tiktok-comments-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 '{ "postURLs": [ "https://www.tiktok.com/@tiktok/video/7106594312292453675" ], "proxyConfiguration": { "useApifyProxy": true } }' | apify call forlex/tiktok-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=forlex/tiktok-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TikTok Comments Scraper ⚡", "description": "Lightning-fast scraper to extract TikTok comments, nested replies, likes, and user data. Includes date filtering and sorting.", "version": "0.1", "x-build-id": "2vr1K2yun6KJJ7Nsv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/forlex~tiktok-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-forlex-tiktok-comments-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/forlex~tiktok-comments-scraper/runs": { "post": { "operationId": "runs-sync-forlex-tiktok-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/forlex~tiktok-comments-scraper/run-sync": { "post": { "operationId": "run-sync-forlex-tiktok-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "postURLs" ], "properties": { "postURLs": { "title": "🔗 TikTok Video URLs", "type": "array", "description": "URLs of TikTok videos", "items": { "type": "string" } }, "maxComments": { "title": "Max Comments", "minimum": 1, "type": "integer", "description": "Maximum number of comments to extract.", "default": 100 }, "maxRepliesPerComment": { "title": "Max Replies Per Comment", "minimum": 0, "type": "integer", "description": "Maximum number of nested replies to extract per top-level comment. Set to 0 to ignore replies.", "default": 0 }, "sortBy": { "title": "Sort By", "enum": [ "Top", "Most Liked", "Most Recent", "Most Replied" ], "type": "string", "description": "How to sort the final extracted comments.", "default": "Top" }, "dateFrom": { "title": "Date From (YYYY-MM-DD)", "type": "string", "description": "Optional: Only extract comments posted on or after this date (e.g. 2024-01-01)." }, "dateTo": { "title": "Date To (YYYY-MM-DD)", "type": "string", "description": "Optional: Only extract comments posted on or before this date (e.g. 2024-12-31)." }, "minLikes": { "title": "Minimum Likes", "minimum": 0, "type": "integer", "description": "Optional: Only extract comments with at least this many likes.", "default": 0 }, "minReplies": { "title": "Minimum Replies", "minimum": 0, "type": "integer", "description": "Optional: Only extract comments with at least this many replies.", "default": 0 }, "proxyConfiguration": { "title": "Proxy Settings", "type": "object", "description": "Select proxies to be used. Residential proxies are highly recommended to avoid TikTok's anti-bot measures." } } }, "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 } } } } } } } } } } ```