Twitter(X) Comment Scraper:Support Sentiment&Tone Analyzer
Pricing
$20.00/month + usage
Twitter(X) Comment Scraper:Support Sentiment&Tone Analyzer
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 (1)
Pricing
$20.00/month + usage
10
Total users
181
Monthly users
33
Runs succeeded
>99%
Issues response
4.4 hours
Last modified
3 days ago
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.
$# Start Server-Sent Events (SSE) session and keep it running<curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=fastcrawler/twitter-x-comment-scraper-support-sentiment-tone-analyzer"
# Session id example output:# event: endpoint# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1faUsing Twitter(X) Comment Scraper:Support Sentiment&Tone Analyzer via Model Context Protocol (MCP) server
MCP server lets you use Twitter(X) Comment Scraper:Support Sentiment&Tone Analyzer within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Twitter(X) Comment Scraper:Support Sentiment&Tone Analyzer Actor with the provided input.
$curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{$ "jsonrpc": "2.0",$ "id": 1,$ "method": "tools/call",$ "params": {$ "arguments": {$ "tweetUrl": "https://x.com/sama/status/1910363426972635455",$ "rankingMode": "Relevance"$},$ "name": "fastcrawler/twitter-x-comment-scraper-support-sentiment-tone-analyzer"$ }$}'The response should be: Accepted. You should received response via SSE (JSON) as:
$event: message$data: {$ "result": {$ "content": [$ {$ "type": "text",$ "text": "ACTOR_RESPONSE"$ }$ ]$ }$}Configure local MCP Server via standard input/output for Twitter(X) Comment Scraper:Support Sentiment&Tone Analyzer
You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:
{ "mcpServers": { "actors-mcp-server": { "command": "npx", "args": [ "-y", "@apify/actors-mcp-server", "--actors", "fastcrawler/twitter-x-comment-scraper-support-sentiment-tone-analyzer" ], "env": { "APIFY_TOKEN": "<YOUR_API_TOKEN>" } } }}You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.
To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.
