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Related Servers

Alternatives to NutriBalance

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables nutrition tracking via AI, allowing users to read food logs with macros, goals, and profile, log meals by text or photo, and access diary, subscription, diabetes, and wearable/glucose data.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Give your AI assistant the ability to analyze food images and look up nutrition data for any food — calories, macros, vitamins, minerals, allergens, and dietary flags in under 1 second — powered by TastyAPI. Much faster and more accurate than Gemini and GPT-4 Vision (4-10 seconds).
      2
      31 npm
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Provides intelligent access to the USDA nutrition database through AI assistants, enabling users to search foods, compare nutritional content, find foods high in specific nutrients, and query authoritative nutrition data across 7,146+ food items through natural language.
      1
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    TDQS

    A4.2/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool targets a distinct phase of nutrition management: calculating metabolic needs (calculate_tdee), retrieving food data (lookup_nutrition), creating eating plans (generate_meal_plan), addressing specific health issues (fix_deficiency), and evaluating dietary quality (nutrition_score). No functional overlap exists between tools.

    Naming Consistency4/5

    Four tools follow a clear verb_noun pattern (calculate_tdee, fix_deficiency, generate_meal_plan, lookup_nutrition) using snake_case. However, nutrition_score breaks the pattern by placing the noun first, creating a minor inconsistency in an otherwise uniform convention.

    Tool Count5/5

    Five tools is an ideal scope for a focused nutrition server, covering the essential workflows (calculation, lookup, planning, deficiency correction, and evaluation) without bloat or unnecessary fragmentation.

    Completeness4/5

    The surface covers the core nutrition lifecycle well: determining needs, sourcing foods, planning meals, correcting deficiencies, and scoring intake. A minor gap exists in exploratory discovery (e.g., searching for foods by nutrient criteria rather than by name), though fix_deficiency partially addresses this for specific nutrients.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues