nutrients-mcp
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Alternatives to nutrients-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityDmaintenanceProvides AI assistants with real-time access to nutrition data from USDA FoodData Central and FatSecret, enabling accurate answers with citations for nutrition queries.-
- FlicenseAqualityDmaintenanceCalculate TDEE & macro targets, look up food nutrition data, generate meal plans, fix nutrient deficiencies, and score a day's eating from 0–100. Free nutrition tools for AI assistants.5-
- FlicenseNot gradedqualityDmaintenanceProvides 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-
- AlicenseNot gradedqualityCmaintenanceEnables 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
- AlicenseBqualityCmaintenanceEnables AI assistants to search for recipes, get nutritional information, find ingredients, and more through the Spoonacular Food API using natural language.632 npm5ISC
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to analyze the nutrition of ingredients or recipe lines and to search recipe and food databases with optional diet, health, and cuisine filters.21 npmMIT
TDQS
Scored across 2 tools
Both tools analyze food and return similar nutritional data, but they are clearly distinguished by input type: one requires an image URL and the other a text name/description. The descriptions make this distinction explicit, so an agent should be able to select the correct tool without confusion.
The tools follow a consistent verb_noun pattern: 'analyze_food' and 'analyze_food_image'. The naming is predictable and clearly indicates a shared core function with a specific modifier for the image variant.
With only two tools, the server feels thin for the domain of nutritional analysis. While both tools are useful, the minimal count limits the server's overall utility and makes it borderline appropriate for its stated purpose.
The two tools cover the two primary input methods for analyzing a food item: image and text description. However, there are minor gaps, such as no batch analysis or retrieval of nutritional data by food ID, but the core workflow of analyzing a single food item is fully supported.