# Tiktok Comments (`shareze001/tiktok-comments`) Actor

Scrape the comments of a certain video under a certain tiktok user through username and videoId.

- **URL**: https://apify.com/shareze001/tiktok-comments.md
- **Developed by:** [shareze](https://apify.com/shareze001) (community)
- **Categories:** Developer tools, Integrations
- **Stats:** 27 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

$9.99/month + usage

To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period. You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#rental-actors

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

This Apify Actor is designed to scrape comments from TikTok videos. It retrieves detailed information about comments, including user details, likes, replies, and more.

### How to Use

1. **Input Configuration**:
   The Actor requires the following input parameters, which are defined in the `input_schema.json` file:
   - `videoId` (string, required): The ID of the TikTok video you want to scrape comments from.
   - `size` (integer, required): The maximum number of comments to retrieve.

2. **Run the Actor**:
   You can run the Actor on the Apify platform or locally using the Apify SDK. Provide the required input parameters in the following format:
   ```json
   {
       "videoId": "7550395004708048141",
       "size": 10
   }

   ```

3. **Output**:
   The Actor will return a JSON array containing the scraped comments. Each comment includes the following fields:
   - `cid`: Comment ID.
   - `text`: The text of the comment.
   - `create_time`: The timestamp when the comment was created.
   - `digg_count`: The number of likes the comment received.
   - `reply_comment_total`: The total number of replies to the comment.
   - `user`: An object containing details about the user who posted the comment:
     - `uid`: User ID.
     - `unique_id`: The unique username of the user.
     - `nickname`: The nickname of the user.
     - `avatar_thumb`: The URL of the user's avatar thumbnail.
   - `image_list`: A list of images included in the comment (if any).

4. **Example Output**:
   ```json
   [
       {
           "cid": "1234567890",
           "text": "Great video!",
           "create_time": 1691234567,
           "digg_count": 100,
           "reply_comment_total": 5,
           "user": {
               "uid": "987654321",
               "unique_id": "user123",
               "nickname": "John Doe",
               "avatar_thumb": "https://example.com/avatar.jpg"
           },
           "image_list": []
       }
   ]
   ```

# Actor input Schema

## `videoId` (type: `string`):

tiktok videoId.

## `size` (type: `integer`):

comment size

## Actor input object example

```json
{
  "videoId": "7671360899193523469",
  "size": 10
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "videoId": "7671360899193523469",
    "size": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("shareze001/tiktok-comments").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "videoId": "7671360899193523469",
    "size": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("shareze001/tiktok-comments").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "videoId": "7671360899193523469",
  "size": 10
}' |
apify call shareze001/tiktok-comments --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,shareze001/tiktok-comments"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/euNTgWXziiQAEY2SJ/builds/vLVahmw2TWa5Wq2g7/openapi.json