Analyze text sentiment, emotions, confidence scores, and key phrases. x402 USDC.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Sentiment Analyzer API.
text_analyze_sentimentAnalyze sentiment of a single text
text_analyze_sentiment_batchAnalyze sentiment of up to 20 texts in batch
textThe text to analyze for sentiment
textsArray of texts to analyze (max 20)
Sentiment analysis with emotion detection, confidence scores, and key phrase extraction. Single or batch mode. Pay-per-call via x402 (USDC on Base L2) -- no API key, no signup, no rate-limit wall.
Part of the klymax402 marketplace -- 100 x402 micropayment APIs for AI agents, one wallet, USDC on Base.
Add to your MCP client config (Claude Desktop, Cursor, ElizaOS, etc.):
Any x402-aware client (@x402/fetch, x402-agent-tools, ATXP) handles the 402 -> sign -> retry cycle automatically.
| Tool | Method | Path | Price | Description |
|---|---|---|---|---|
text_analyze_sentiment | POST | /api/analyze | $0.015 | Analyze sentiment of a single text |
text_analyze_sentiment_batch | POST | /api/analyze/batch | $0.10 | Analyze sentiment of up to 20 texts in batch |
text_analyze_sentimentUse this when you need to determine the emotional tone and sentiment of text. Returns structured sentiment analysis with emotion breakdown and key drivers.
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
text | string | yes | The text to analyze for sentiment |
Returns
sentiment -- overall sentiment label (positive, negative, neutral)confidence -- confidence score 0-100emotions -- detected emotions with scores (joy, anger, fear, surprise, sadness)keyPhrases -- array of phrases driving the sentimentscore -- numeric sentiment score from -1.0 (negative) to 1.0 (positive)Example response:
When to use: responding to customer feedback, reviews, or social media mentions. Essential for brand monitoring, support ticket triage, and content tone analysis.
text_analyze_sentiment_batchUse 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.
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
texts | array | yes | Array of texts to analyze (max 20) |
Returns
results -- array of sentiment objects, one per input textaverageSentiment -- overall average sentiment score across all textsdistribution -- count of positive/negative/neutral textsExample response:
When to use: bulk analysis of reviews, survey responses, or social media feeds. Essential when comparing sentiment across multiple data points.
eip155:8453)100 x402 micropayment APIs for AI agents -- one wallet, USDC on Base, zero signup.
MIT
Factual signals from GitHub, npm, and our automated checks β not a rating.
No reviews yet β be the first to share how this listing worked for you.
Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.
[](https://allmcps.com/mcp/sentiment-analyzer-api)<a href="https://allmcps.com/mcp/sentiment-analyzer-api"><img src="https://allmcps.com/api/badge/sentiment-analyzer-api?style=directory" alt="Sentiment Analyzer API on AllMCPs" /></a>