BMI & Fitness Metrics Skill

Overview

BMI Calculator uses the Mifflin-St Jeor equation for accurate BMR calculations and evidence-based activity multipliers for TDEE. It provides actionable data for fitness apps, health trackers, and nutrition planning tools.

Live Test BMI & Fitness Metrics Skill Skill →

The tool

Once your client is connected to the VerveKit server, this appears in its tool list as BMIFitnessMetricsSkill. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.

{
  "name": "BMIFitnessMetricsSkill",
  "arguments": {
    "weight": "180",
    "height": "70",
    "unit": "imperial"
  }
}

You do not name the tool yourself; the model picks it. Asking about 180 in the terms this skill covers is enough for it to reach for BMIFitnessMetricsSkill on its own — naming it explicitly also works, and is the way to force the call.

Connecting

One server URL covers every skill in the catalog, including this one. Authorization is OAuth: the client opens a browser once, and there is no key to paste into a config file.

{
  "mcpServers": {
    "vervekit": {
      "url": "https://api.vervekit.com/v1/mcp"
    }
  }
}

https://api.vervekit.com/v1/mcp

Per-client setup — Claude, Cursor, VS Code, ChatGPT — is on the MCP setup page.

Arguments

These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made. Premium arguments are accepted on every plan but only take effect on plans that include them.

What the model gets back

The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.

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{
  "status": "ok",
  "error": null,
  "data": {
    "height": "70 inches",
    "weight": "180 lbs",
    "bmi": 25.83,
    "bmiPrime": 1.033,
    "category": "Overweight",
    "risk": "Increased risk",
    "summary": "BMI is above the healthy range. Lifestyle changes may be beneficial.",
    "idealWeightRange": {
      "min": 129,
      "max": 173.5,
      "unit": "lbs"
    },
    "weightToChange": {
      "direction": "lose",
      "amount": 6.5,
      "unit": "lbs"
    },
    "bmr": 1783,
    "tdee": 2763,
    "calorieTargets": {
      "extremeDeficit": 1763,
      "moderateDeficit": 2263,
      "maintain": 2763,
      "moderateSurplus": 3063,
      "bulkSurplus": 3263
    },
    "macros": {
      "lose": {
        "protein": 198,
        "carbs": 198,
        "fat": 75
      },
      "maintain": {
        "protein": 207,
        "carbs": 276,
        "fat": 92
      },
      "gain": {
        "protein": 230,
        "carbs": 345,
        "fat": 85
      }
    }
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Failure modes

Errors come back as tool errors carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.

A call costs 2 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

Fitness Apps

Calculate BMI, BMR, TDEE and macro targets for users tracking their fitness journey.

Health Tracking

Provide users with their ideal weight range and how much to gain or lose to reach a healthy BMI.

Nutrition Planning

Generate personalized calorie and macronutrient targets for meal planning applications.

Weight Loss Programs

Calculate calorie deficits and protein targets for weight loss applications.

Other ways to use BMI & Fitness Metrics Skill

Set up BMI & Fitness Metrics Skill on VerveKit, or reach the same source a different way. Your VerveKit account and credits work on all of them — one key, one balance.

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