CalorieNinjas

Name: CalorieNinjas API
Brand: CalorieNinjas
Availability: InStock

✓ Official Vendor SpecData EnrichmentData TransformationapiKey1 EndpointsREST

For Agents

Convert free-text food descriptions into structured nutrition records via a single natural-language endpoint.

Quickstart

Get started with CalorieNinjas in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"extract nutrition from a meal description"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with CalorieNinjas API.

Parse free-text meal descriptions into individual food items with serving quantities

Return calories, protein, fat, carbohydrates, fiber, sugar, sodium, potassium, and cholesterol per parsed item

Handle mixed quantity formats including cups, ounces, grams, and natural counts in a single query

Power chat- or voice-first meal logging where users describe meals conversationally

GET STARTED

Start building with CalorieNinjas API

Explore with Jentic

View OpenAPI Document

Use for: Extract nutrition data from a meal description, Calculate calories for a free-text food query, Get protein and fat values from a typed meal log, I want to parse '2 eggs and a slice of toast' into nutrition values

Not supported: Does not handle recipe generation, food image recognition, or barcode scanning — use for parsing free-text food descriptions into nutrition values only.

CalorieNinjas is a natural-language nutrition API that extracts structured calorie and macronutrient data from any free-text food description. A single GET /v1/nutrition endpoint accepts a query string such as '1 cup rice and 10 oz chicken breast' and returns parsed items with calories, protein, fat, carbohydrates, fiber, sugar, sodium, potassium, and cholesterol per item. It is designed for chatbots, voice assistants, and meal-tracking apps that need to convert spoken or typed meals into structured nutrition records.

Use Cases

Patterns agents use CalorieNinjas API for, with concrete tasks.

★ Conversational Meal Logging

Chatbots and voice assistants accept meals in natural language ('I had a turkey sandwich and a banana for lunch') and need to convert that text into structured nutrition values. CalorieNinjas's single /v1/nutrition endpoint parses the query string and returns each item with full macronutrient detail, removing the need to maintain a food-name dictionary.

Send GET /v1/nutrition with query='turkey sandwich and a banana' and return the total calories and protein across the parsed items.

Recipe Ingredient Nutrition Breakdown

Recipe apps often store ingredients as free-text lines such as '1 cup flour' or '200g chicken'. Passing the full ingredient list to /v1/nutrition returns one nutrition record per parsed line, letting the app compute per-recipe and per-serving totals without an ingredient lookup table.

Send GET /v1/nutrition with the full ingredient list for a 4-serving recipe, sum the calories returned, and divide by 4 to report per-serving calories.

Diet Coaching Bot Quick Estimates

Diet-coaching agents need to give users an instant calorie estimate for a meal they are about to eat. A single call to /v1/nutrition with the meal description returns calories, sugar, and sodium values that the bot can compare against the user's daily target before the meal is logged.

Send GET /v1/nutrition with query='large pepperoni pizza slice' and warn the user if returned sodium exceeds 800 mg.

AI Agent Nutrition Workflows via Jentic

Through Jentic, an agent searches for 'extract nutrition from text', loads the /v1/nutrition input schema, and executes the call without managing the api_key header. Jentic's vault holds the API key so it never appears in the agent's prompt or logs.

Use the Jentic SDK to search 'extract nutrition from text', load the /v1/nutrition operation, and execute it with a user-provided meal description.

Key Endpoints

1 endpoints — calorieninjas is a natural-language nutrition api that extracts structured calorie and macronutrient data from any free-text food description.

METHOD

PATH

DESCRIPTION

GET

/v1/nutrition

Parse a free-text query and return per-item nutrition values

GET

/v1/nutrition

Parse a free-text query and return per-item nutrition values

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

The CalorieNinjas API key is stored encrypted in the Jentic vault. Agents receive scoped execution rights and Jentic injects the key into the api_key header at call time, so the raw key never enters the agent's context.

Intent-based discovery

Agents search by intent (for example, 'extract nutrition from text') and Jentic returns the GET /v1/nutrition operation with its input schema, so the agent can call it directly with a user-provided query.

Time to first call

Direct CalorieNinjas integration: a few hours to wire the API key header and parse the response array. Through Jentic: under 30 minutes to search, load, and execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Edamam Food and Nutrition API

Edamam offers natural-language nutrition parsing plus a structured food and recipe database, where CalorieNinjas focuses on a single text-to-nutrition endpoint.

Choose Edamam when the agent also needs recipe analysis or a structured food catalog; choose CalorieNinjas for the simplest possible text-to-nutrition call.

Alternative

Nutritionix API

Nutritionix combines natural-language calorie estimation with a branded-foods catalog, where CalorieNinjas exposes only the natural-language endpoint.

Use Nutritionix when the agent needs branded product lookups alongside text parsing; use CalorieNinjas for a lightweight one-call integration.

Complementary

Spoonacular API

Spoonacular generates recipes and meal plans that pair with CalorieNinjas's free-text nutrition extraction for end-to-end meal logging.

Pair Spoonacular for recipe generation with CalorieNinjas for parsing user-typed meals into nutrition records.

FAQs

Specific to using CalorieNinjas API through Jentic.

What authentication does the CalorieNinjas API use?

It uses an API key passed in the api_key HTTP header. Through Jentic, the key is stored in the Jentic vault and injected into the api_key header at execution time, so the raw key never enters the agent's prompt context.

Can I parse a multi-item meal description in one call?

Yes. The single GET /v1/nutrition endpoint accepts a query string containing multiple items, for example '1 cup rice and 10 oz chicken breast', and returns one nutrition record per parsed item in the response array.

Which nutrients does the response return?

Each parsed item includes calories, protein, fat (total and saturated), carbohydrates, fiber, sugar, sodium, potassium, and cholesterol, along with the serving size in grams. Match items by name in the response when summing totals.

How do I integrate CalorieNinjas through Jentic?

Run pip install jentic, then use the SDK to search 'extract nutrition from text'. Jentic returns the GET /v1/nutrition operation with its input schema, so the agent can load and execute it with a user query without browsing the CalorieNinjas docs.

Are there rate limits on the CalorieNinjas API?

The OpenAPI specification does not document rate limits. CalorieNinjas applies plan-based limits at the API key level, so check the dashboard tied to your key for the exact ceiling. Jentic surfaces 429 responses unchanged for your agent to back off.

Is the CalorieNinjas API free?

CalorieNinjas offers a free tier with a monthly request quota plus paid tiers for higher volumes. Pricing details are not in the OpenAPI spec; check calorieninjas.com for current limits and tier pricing.