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Saylor Innovations Body Fat Calculator (US Navy Method)
x402
Saylor Innovations Body Fat Calculator (US Navy Method) is a paid API for AI agents from saylorinnovations.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Calculates body fat percentage from tape measurements using the US Navy formula, returning ACE category, healthy range, and optionally fat and lean mass in kg
Price / call$0.01
Success—
StatusUnknown
How this service works
Body fat percentage from tape measurements using the US Navy method with ACE category, healthy range and fat and lean mass when weight is supplied
Output
Returns a JSON object with the computed body fat percentage, the ACE category (e.g. Fitness, Acceptable, Obese), the healthy range as a percentage string, the method and source used, the inputs echoed back, and — if weight was provided — fat mass and lean mass in kilograms, plus an optional note for context.
Example use cases
Personal body composition check
“I want to know my body fat percentage and what category I fall into — I'm female, 165 cm tall, my neck is 33 cm, waist is 72 cm, and hips are 95 cm. I weigh 62 kg so also tell me my fat and lean mass.”
Fitness app integration for clients
“Calculate body fat for a male client who is 183 cm tall, has a 40 cm neck and 90 cm waist — he weighs 88 kg. I need the category, healthy range, and both fat mass and lean mass.”
Military or sports readiness assessment
“Run a US Navy body fat check on me: I'm male, 175 cm, neck circumference 37 cm, waist 82 cm. Just give me the percentage and whether I'm in the healthy range.”
Technical details
Endpoint
GEThttps://saylorinnovations.com/api/health/body-fat?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, formula-based body fat estimate from simple tape measurements without requiring expensive lab tests or body scan equipment. It is ideal for fitness, wellness, or health-tracking agents that need to classify body composition using the widely-accepted US Navy method. Prefer it over BMI-based endpoints when you want a more accurate fat-vs-lean breakdown, and over DEXA or bioimpedance APIs when only circumference measurements are available.
Side effects
- Missing required query parameters (sex, height_cm, neck_cm, waist_cm) result in an error response
- Invalid or non-numeric values for measurements may cause calculation failure
- Unrealistic measurement values (e.g. neck larger than waist) may produce nonsensical but technically computed results
- Hip measurement may be required for female calculations — omitting it for female inputs could cause an error
- Network or upstream service downtime returns a non-200 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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