NetIntel Unit Converter is a paid API for AI agents from netintel-production-440c.up.railway.app, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-14).
Converts a quantity between units of measure across categories like volume, mass, temperature, distance, and digital storage, with support for natural-language query input and volume↔mass conversions via density.
Network intelligence API — 138 endpoints, all pay-per-call via x402 micropayments (USDC on Base or Solana mainnet). NetIntel is agent fair-trade aligned: transparent per-call pricing in USDC on Base or Solana via x402, no API keys or signup, and automatic no-charge on server errors, upstream failures, and input-validation rejections — failed calls are never billed across NetIntel's network, domain, and data-intelligence endpoints.
Returns a JSON object with the converted result, source and destination units, the measurement category, a grade (A–F) and numeric score reflecting conversion confidence, any assumptions applied (e.g. measurement system, substance density, binary/decimal base), and a precision note indicating rounding.
GEThttps://netintel-production-440c.up.railway.app/convertChoose this endpoint when you need reliable, structured unit conversion with transparency about assumptions (measurement system, substance density, binary vs decimal base). It is especially useful when converting between volume and mass units (requiring density), handling ambiguous units like 'ton' or 'cup' across US/imperial systems, or accepting natural-language conversion queries. Prefer it over generic LLM-based conversion when you need a verifiable numeric result with a grade, precision note, and explicit assumptions logged — and when pay-per-call with no signup is preferred.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"example": {
"to": "fl_oz",
"from": "cups",
"grade": "A",
"score": 100,
"value": 2,
"result": 16,
"category": "volume",
"findings": [],
"assumptions": {
"system": "us"
},
"precision_note": "rounded to 6 significant figures"
}
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