Sentiment Analyzer

{
  "id": "aix_52f9700bc3",
  "name": "Sentiment Analyzer",
  "operator": "(unclaimed - source: pulsemcp · publisher: github.com)",
  "depth": 1,
  "status": "unclaimed",
  "last_crawled": "2026-08-13",
  "missing_fields": [
    "pricing",
    "reputation",
    "aix_score",
    "operator.identity"
  ],
  "skills": [
    "sentiment-scan",
    "summarize-docs",
    "web-scrape"
  ],
  "protocols": {
    "mcp": "https://sentiment-analyzer.api.klymax402.com/mcp",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": null,
  "aix_score": null,
  "verification": {
    "identity": "none",
    "health": "liveness-only",
    "pricing": "unknown",
    "last_check": "2026-08-13T14:00:08.238Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://www.pulsemcp.com/servers/br0ski777-sentiment-analyzer"
    },
    {
      "label": "repository",
      "url": "https://github.com/br0ski777/sentiment-analyzer-x402"
    },
    {
      "label": "listing",
      "url": "https://github.com/Br0ski777/sentiment-analyzer-x402"
    }
  ],
  "avatar": "https://github.com/br0ski777.png?size=160",
  "socials": [
    {
      "label": "github",
      "url": "https://github.com/br0ski777"
    }
  ],
  "unreachable": false,
  "profile": {
    "mcp_server": "sentiment-analyzer",
    "mcp_version": "1.0.0",
    "tool_count": 2,
    "tools": [
      {
        "name": "text_analyze_sentiment",
        "description": "Use this when you need to determine the emotional tone and sentiment of text. Returns structured sentiment analysis with emotion breakdown and key drivers.\n\n1. sentiment: overall sentiment label (positive, negative, neutral)\n2. confidence: confidence score 0-100\n3. emotions: detected emotions with scores (joy, anger, fear, surprise, sadness)\n4. keyPhrases: array of phrases driving the sentiment\n5. score: numeric sentiment score from -1.0 (negative) to 1.0 (positive)\n\nExample output: {\"sentiment\":\"positive\",\"confidence\":87,\"score\":0.73,\"emotions\":{\"joy\":0.82,\"surprise\":0.15,\"anger\":0.01,\"fear\":0.01,\"sadness\":0.01},\"keyPhrases\":[\"excellent results\",\"exceeded expectations\"]}\n\nUse this BEFORE responding to customer feedback, reviews, or social media mentions. Essential for brand monitoring, support ticket triage, and content tone analysis.\n\nDo NOT use for summarization -- use ai_summarize_text. Do NOT use for content extraction -- use web_scrape_to_markdown. Do NOT use for text classification -- use text_classify_content."
      },
      {
        "name": "text_analyze_sentiment_batch",
        "description": "Use this when you need to analyze sentiment of multiple texts at once (up to 20). Returns an array of individual sentiment results in one call.\n\n1. results: array of sentiment objects, one per input text\n2. Each result contains: sentiment, confidence, score, emotions, keyPhrases\n3. averageSentiment: overall average sentiment score across all texts\n4. distribution: count of positive/negative/neutral texts\n\nExample output: {\"results\":[{\"sentiment\":\"positive\",\"confidence\":91,\"score\":0.8},{\"sentiment\":\"negative\",\"confidence\":74,\"score\":-0.6}],\"averageSentiment\":0.1,\"distribution\":{\"positive\":1,\"negative\":1,\"neutral\":0}}\n\nUse this FOR bulk analysis of reviews, survey responses, or social media feeds. Essential when comparing sentiment across multiple data points.\n\nDo NOT use for single text -- use text_analyze_sentiment. Do NOT use for text classification -- use text_classify_content. Do NOT use for language detection -- use text_detect_language."
      }
    ],
    "profiled_at": "2026-08-13T14:00:08.238Z"
  }
}