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$4.99 / 1,000 results

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TikTok Comment Scraper

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Developed by

PowerAI

Extract TikTok video comments with comprehensive metadata including user profiles, engagement metrics, and reply information. Perfect for sentiment analysis, audience research, and content feedback analysis. Supports pagination for large-scale data collection.

5.0 (1)

Pricing

$4.99 / 1,000 results

Total users

Monthly users

Runs succeeded

>99%

Last modified

25 days ago

Social media

Videos

For creators

You can access the TikTok Comment Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
    "mcpServers": {
        "local-actors-mcp-server": {
            "command": "npx",
            "args": [
                "-y",
                "@apify/actors-mcp-server",
                "--actors",
                "powerai/tiktok-comment-scraper"
            ],
            "env": {
                "APIFY_TOKEN": "<YOUR_API_TOKEN>"
            }
        }
    }
}

Configure MCP server with TikTok Comment Scraper

You can interact with the MCP server via standard input/output - stdio (as shown above), which is ideal for local integrations and command-line tools such as the Claude desktop client, or you can interact with the server through Server-Sent Events (SSE) to send messages and receive responses, which looks as follows:

{
    "mcpServers": {
        "remote-actors-mcp-server": {
            "type": "sse",
            "url": "https://mcp.apify.com/sse?actors=powerai/tiktok-comment-scraper",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other supported MCP client of your choice.

If you want to learn more about our Apify MCP implementation, check out our MCP documentation. To learn more about the Model Context Protocol in general, refer to the official MCP documentation or read our blog post.

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