Sentiment Analysis MCP
Sentiment, emotion, and intent analysis for text using local AI. Returns polarity score, 6 emotional dimensions (joy, fear, anger, sadness, surprise, disgust), intent classification, and key sentiment drivers.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
text |
string | ✅ | Input text to analyze |
granularity |
string | ❌ | document, sentence, or aspect (default: document) |
aspects |
array | ❌ | Specific aspects to score (e.g., ["price", "quality", "service"]) |
language |
string | ❌ | ISO language code (auto-detected) |
Example Response
{
"sentiment": {"label": "negative", "score": -0.72, "confidence": 0.94},
"emotions": {
"anger": 0.61, "disgust": 0.44, "fear": 0.23,
"joy": 0.05, "sadness": 0.38, "surprise": 0.12
},
"intent": "complaint",
"aspects": {
"price": {"sentiment": "negative", "score": -0.85},
"quality": {"sentiment": "neutral", "score": 0.02},
"service": {"sentiment": "negative", "score": -0.91}
},
"key_phrases": ["overpriced", "rude staff", "never coming back"]
}
Use Cases
- Customer support ticket prioritization by emotional intensity
- Product review brand health monitoring
- Social media crisis detection for PR teams
Access
# x402 endpoint — pay $0.01 USDC per call (Base mainnet)
POST https://x402.ntriq.co.kr/sentiment
# Service catalog
curl https://x402.ntriq.co.kr/services
x402 micropayments — USDC on Base, gasless EIP-3009