Sentiment Analyzer API

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.

Quickstart -- MCP

Add to your MCP client config (Claude Desktop, Cursor, ElizaOS, etc.):

{
  "mcpServers": {
    "sentiment-analyzer": {
      "url": "https://sentiment-analyzer.api.klymax402.com/mcp"
    }
  }
}

Related MCP server: ntriq-agentshop

Quickstart -- HTTP (x402)

curl -X POST "https://sentiment-analyzer.api.klymax402.com/api/analyze" \
  -H "Content-Type: application/json" \
  -d '{"text":"..."}'
# -> 402 Payment Required, with an x402 payment challenge in the response body

Any x402-aware client (@x402/fetch, x402-agent-tools, ATXP) handles the 402 -> sign -> retry cycle automatically.

Tools

text_analyze_sentiment

Use this when you need to determine the emotional tone and sentiment of text. Returns structured sentiment analysis with emotion breakdown and key drivers.

Parameters

Returns

• sentiment -- overall sentiment label (positive, negative, neutral)

• confidence -- confidence score 0-100

• emotions -- detected emotions with scores (joy, anger, fear, surprise, sadness)

• keyPhrases -- array of phrases driving the sentiment

• score -- numeric sentiment score from -1.0 (negative) to 1.0 (positive)

Example response:

{"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"]}

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_batch

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.

Parameters

Returns

• results -- array of sentiment objects, one per input text

• averageSentiment -- overall average sentiment score across all texts

• distribution -- count of positive/negative/neutral texts

Example response:

{"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}}

When to use: bulk analysis of reviews, survey responses, or social media feeds. Essential when comparing sentiment across multiple data points.

Example agent prompts

• "Determine the emotional tone and sentiment of text"

• "Analyze sentiment of multiple texts at once (up to 20)"

Payment

• Protocol: x402 -- HTTP-native pay-per-call, no signup, no API key

• Network: Base L2 (eip155:8453)

• Asset: USDC

• Facilitator: Coinbase CDP (primary), PayAI (fallback)

• Also reachable via ATXP (OAuth-wrapped x402, RFC 9728 protected-resource metadata)

Part of klymax402

100 x402 micropayment APIs for AI agents -- one wallet, USDC on Base, zero signup.

• Catalog: https://klymax402.com/llms.txt

• Full API reference: https://klymax402.com/llms-full.txt

• Live stats: https://klymax402.com/stats

License

MIT