Nutritionix API

Name: Nutritionix API API
Brand: Nutritionix API
Availability: InStock

✓ Official Vendor SpecData EnrichmentData TransformationapiKey7 EndpointsREST

For Agents

Turn natural-language food and exercise descriptions into structured nutrition and calorie data, plus search a verified database of common, branded, and restaurant foods.

Connect the Nutritionix API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Nutritionix API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Install Jentic One Beta (Self-Hosted)

Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Nutritionix API API.

Parse natural-language meal descriptions into per-food macro and micronutrient values

Estimate calories burned for natural-language exercise descriptions using user weight and duration

Run instant typeahead-style search across common, branded, and restaurant foods

Look up a specific food item by Nutritionix ID or UPC barcode

GET STARTED

Start building with Nutritionix API API

Explore with Jentic

View OpenAPI Document

The Nutritionix API exposes a verified nutrition database covering common foods, branded packaged products, and restaurant menu items, with detailed macro and micronutrient breakdowns. Its standout feature is natural-language parsing — a developer can send a phrase like '2 eggs and a slice of toast' and receive structured nutrient data back, alongside the same treatment for exercise calorie estimation. It also exposes instant search for foods, lookup by item or UPC, and a directory of restaurant locations and brands. The surface is small at seven endpoints, which makes it well suited to nutrition logging, fitness coaching, and meal-planning agents.

Use Cases

Patterns agents use Nutritionix API API for, with concrete tasks.

★ Natural-Language Food Logging

Power a nutrition-tracking app or chatbot that accepts free-text meal entries — for example 'a banana and a cup of oat milk' — and returns calories, macronutrients, and serving information per food. Nutritionix handles the tokenisation, quantity parsing, and nutrient lookup against its verified database, so the developer does not need a custom NLP pipeline. Setup is typically under a day with the natural-language endpoint and an x-app-id/x-app-key pair.

Send POST /natural/nutrients with the query 'two scrambled eggs and avocado toast' and return total calories and protein.

Exercise Calorie Estimation

Estimate calories burned for free-text exercise descriptions like '30 minutes of cycling' using weight, age, and gender to scale results. This is well suited to fitness journaling apps, coaching agents, and wearable companion experiences that need a quick estimate without bundling a metabolic-equation library. The endpoint accepts the same conversational style as the food parser, keeping the integration consistent.

Send POST /natural/exercise with 'ran 5 km in 28 minutes' and a weight of 75 kg, then return the estimated calories burned.

Restaurant Menu Lookups

Build a recommendation flow that helps users pick lower-calorie items at chain restaurants by searching foods filtered to a specific brand and pulling locations nearby. Nutritionix indexes thousands of branded restaurant items, so an agent can answer 'what are the lightest menu items at Sweetgreen?' with structured nutrient data rather than scraped HTML.

Call GET /search/instant with 'sweetgreen kale caesar', then GET /search/item to retrieve the full nutrient profile for the top match.

Agent-Driven Nutrition Coaching

Let an AI agent answer 'how many calories were in what I just ate?' by chaining the natural-nutrients endpoint with item lookups, all behind a single intent. Through Jentic, the agent searches by intent and gets only the operations it needs, with API credentials handled by the platform.

Search Jentic for 'log a meal in natural language', load the operation, and return total kilojoules for the user's lunch description.

Key Endpoints

7 endpoints — the nutritionix api exposes a verified nutrition database covering common foods, branded packaged products, and restaurant menu items, with detailed macro and micronutrient breakdowns.

METHOD

PATH

DESCRIPTION

POST

/natural/nutrients

Parse a natural-language meal into nutrients

POST

/natural/exercise

Estimate calories burned from a natural-language exercise

GET

/search/instant

Instant food search across common and branded items

GET

/search/item

Look up an item by Nutritionix ID or UPC

GET

/locations

Search restaurant locations near a coordinate

GET

/brands/{brandId}

Retrieve brand details by ID

POST

/natural/nutrients

Parse a natural-language meal into nutrients

POST

/natural/exercise

Estimate calories burned from a natural-language exercise

GET

/search/instant

Instant food search across common and branded items

GET

/search/item

Look up an item by Nutritionix ID or UPC

GET

/locations

Search restaurant locations near a coordinate

Why though Jentic?

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

Credential isolation

Both x-app-id and x-app-key are stored encrypted in the Jentic vault. Agents receive scoped access — neither header value is exposed to the agent's context.

Intent-based discovery

Agents search Jentic with phrases like 'log a meal in natural language' or 'estimate calories burned'. Jentic returns the matching operation and its input schema so the agent can call the correct endpoint without browsing the docs.

Time to first call

Direct integration: 1-2 days for header auth, request shaping, and response normalisation. Through Jentic: under an hour — search, load, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Edamam Nutrition API

Recipe and food nutrition analysis with detailed diet labels — competing nutrition data source.

Choose Edamam when the use case centres on recipe-level analysis or diet labelling rather than branded restaurant items.

Alternative

Spoonacular Food API

Food, recipe, and meal-planning API with broader recipe coverage than Nutritionix.

Choose Spoonacular when the agent also needs recipes, meal plans, or wine pairings, not just nutrient lookup.

Complementary

OpenAI API

Pair with a chat-completion model to extract intent before calling Nutritionix natural-nutrients.

Use when the agent needs to disambiguate vague meal descriptions before querying Nutritionix.

FAQs

Specific to using Nutritionix API API through Jentic.

What authentication does the Nutritionix API use?

The API requires two API key headers: x-app-id and x-app-key, issued from the Nutritionix developer dashboard. There is no OAuth flow — both values are sent on every call. Through Jentic, both keys live in the encrypted vault and are injected at execution time so the agent never holds them directly.

Can I parse a free-text meal into nutrients?

Yes. Send the text in the 'query' field of POST /natural/nutrients and the API returns one foods entry per recognised item with calories, macronutrients, and serving information. The same pattern applies to POST /natural/exercise for workout descriptions.

What are the rate limits for the Nutritionix API?

The OpenAPI spec does not embed explicit limits. Free developer keys are throttled to a low daily call ceiling and the team's published policy is to upgrade to a paid plan for higher throughput. Treat HTTP 429 as a signal to back off.

How do I look up a barcode through Jentic?

Run pip install jentic, then search for 'look up a food by UPC'. Jentic returns GET /search/item with its input schema; pass the upc parameter and execute. The x-app-id and x-app-key headers are attached automatically from your stored credentials at https://app.jentic.com/sign-up.

Does the API include exercise tracking?

Yes — POST /natural/exercise estimates calories burned from a free-text description such as 'biked for 45 minutes', adjusted by user weight, age, height, and gender supplied in the request body.