Pricing

$20.00/month + usage

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Twitter(X) Comment Scraper:Support Sentiment&Tone Analyzer

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Developed by

fastcrawler

Capture all Twitter replies, including hidden and nested ones that conversation ID methods often miss. With advanced sentiment and tone analysis, quickly sort replies by likes, relevance, or emotion. No cookies required. Fast, accurate, and ideal for complete conversation scraping.

5.0 (2)

Pricing

$20.00/month + usage

Total users

233

Monthly users

Runs succeeded

>99%

Issues response

1.3 hours

Last modified

5 hours ago

Social media

Agents

You can access the Twitter(X) Comment Scraper:Support Sentiment&Tone Analyzer 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": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/sse?actors=fastcrawler/twitter-x-comment-scraper-support-sentiment-tone-analyzer",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with Twitter (X) Reply Scraper: Fetch elonmusk Latest 100 Replies

You have a few options for interacting with the MCP server:

Use mcp.apify.com via mcp-remote from your local machine to connect and authenticate using OAuth or an API token (as shown in the JSON configuration above).
Set up the connection directly in your MCP client UI by providing the URL https://mcp.apify.com/sse?actors=fastcrawler/twitter-x-comment-scraper-support-sentiment-tone-analyzer along with an API token (or use OAuth).
Connect to mcp.apify.com via Server-Sent Events (SSE), as shown below:

{
    "mcpServers": {
        "apify": {
            "type": "sse",
            "url": "https://mcp.apify.com/sse?actors=fastcrawler/twitter-x-comment-scraper-support-sentiment-tone-analyzer",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other 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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