API Hub MCP — 337+ Tools

metabolic_age_calc

Calculate your metabolic age by comparing your BMR-based metabolic age to your chronological age. Input BMR, age, and sex to assess metabolic health.

Instructions

Compare BMR-based metabolic age to chronological age.

Parameters:
    bmr — BMR in calories/day.
    age — Chronological age in years.
    sex — 'male' (default) or 'female'.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "bmr": "<bmr>",
      "age": "<age>"
    },
    "name": "metabolic_age_calc"
  }
}

Input Schema

Name	Required	Default
`bmr`	Yes
`age`	Yes
`sex`	No	male

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.4.1Jun 22, 2026

TDQS

A3.5/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not mention any assumptions, limitations, or output details (e.g., what constitutes 'metabolic age'). The output schema exists but the description doesn't reference it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: one line stating the purpose, followed by a clear parameter list. Every sentence earns its place, and there is no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and the presence of an output schema (context indicates it exists), the description provides enough to understand inputs and purpose. However, it lacks details about the output format, formula, or any edge cases, which would be helpful for complex usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaningful context to all three parameters: it specifies units for bmr ('calories/day'), clarifies age as chronological, and defines sex options with a default. This adds value beyond the schema, which only has titles and types. Schema coverage is 0%, so the description compensates well.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Compare BMR-based metabolic age to chronological age.' It uses a specific verb ('Compare') and identifies the resource ('BMR-based metabolic age' vs. 'chronological age'), which distinguishes it from sibling tools like bmr_calc or fitness_age_calc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, restrictions, or scenarios where the tool is or isn't appropriate. For a calculation tool, this is a gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server