Tone Analyzer API

POST https://api.findutils.com/api/tools/tone-analyzer/execute

Analyze the emotional tone of English text with a rule-based word dictionary and return tone scores (joy, sadness, anger, fear, confidence, analytical, tentative, polite), the dominant tone, an overall sentiment with a 0-100 score, and a formality level. Needs at least 5 words. No AI model involved.

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Request body

application/json

text

string required

The text to analyse (at least 5 words).

Example arguments

Verified

{
  "text": "I am so happy and excited about this wonderful news!"
}

curl -X POST https://api.findutils.com/api/tools/tone-analyzer/execute \
  -H "Content-Type: application/json" \
  -d '{
    "text": "I am so happy and excited about this wonderful news!"
  }'

const response = await fetch('https://api.findutils.com/api/tools/tone-analyzer/execute', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({"text":"I am so happy and excited about this wonderful news!"}),
});
const data = await response.json();

import requests

response = requests.post(
    "https://api.findutils.com/api/tools/tone-analyzer/execute",
    json={"text":"I am so happy and excited about this wonderful news!"},
)
data = response.json()

$ch = curl_init('https://api.findutils.com/api/tools/tone-analyzer/execute');
curl_setopt_array($ch, [
    CURLOPT_POST => true,
    CURLOPT_HTTPHEADER => ['Content-Type: application/json'],
    CURLOPT_POSTFIELDS => '{"text":"I am so happy and excited about this wonderful news!"}',
    CURLOPT_RETURNTRANSFER => true,
]);
$data = json_decode(curl_exec($ch), true);

Also an MCP tool

Call tone_analyzer from Claude, Cursor or any MCP client. Same arguments, same output.

https://mcp.findutils.com

MCP reference

Rate limit: 60 a minute, per IP
Auth: None
REST id: tone-analyzer
MCP name: tone_analyzer
Category: Text
Machine-readable: openapi.json · markdown.md

Request body

Example arguments

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