MCP For Claude Marketplace
Nutritional Estimator

Nutritional Estimator MCP Connector for Claude

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Calculate total and per-serving macro and calorie content of recipes using weight-based nutritional density data.

3 tools Official Updated Jun 28, 2026 Official Vinkius Partner
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The Nutritional Estimator MCP server allows AI agents to transform ingredient masses into precise nutritional insights. By leveraging a local database of nutrient densities (standardized per 100g), the tool can aggregate the total calories, proteins, fats, carbohydrates, and fiber for an entire recipe batch or a single serving. Use search_ingredients to find items in the registry, get_ingredient_details to inspect specific nutritional profiles, and compute_recipe_nutrition to perform complex scaling calculations based on provided weights.

macroscaloriesrecipedietarynutrition-calculator

3 tools expose this connector's capabilities to your AI agent.

compute_recipe_nutrition

Calculate total and per-serving nutrition for a recipe

get_ingredient_details

Get nutritional details for an ingredient

search_ingredients

Returns a list of matches. Search for ingredients in the database

See how to talk to your AI agent using Nutritional Estimator.

Find me some ingredients that contain 'apple'.

I found the following matches: Apple (ID: apple_01), Green Apple (ID: green_apple_02), and Apple Juice (ID: apple_juice_03).

What are the nutritional details for ingredient 'chicken_breast'?

For 100g of chicken breast, the nutrition profile is: 165 calories, 31g protein, 3.6g fat, 0g carbs, and 0g fiber.

Calculate the nutrition for a recipe with 200g of chicken_breast and 100g of rice, serving 2 people.

The total recipe contains 430 calories, 65g protein, 7.2g fat, and 78g carbs. Each of the 2 servings provides 215 calories, 32.5g protein, 3.6g fat, and 39g carbs.

The system uses a 100g reference standard. It scales the nutrient values of each ingredient by its weight in grams relative to that 100g base, then sums all contributions for the total recipe and divides by the number of servings for per-portion data.

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