Install Jentic One Beta

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.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fnutritionix.com%2Fnutritionix" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fnutritionix.com%2Fnutritionix" | 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.

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

Retrieve the master list of nutrient codes used across responses

GET STARTED

Start building with Nutritionix API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Nutritionix 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

GET

/brands/{brandId}

Retrieve brand details by ID

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring Nutritionix by hand means sending two headers on every call, x-app-id and x-app-key, against trackapi.nutritionix.com and handling the request plumbing yourself. Through Jentic you install once, import Nutritionix from the API Directory, store both credentials once, and your agent calls it.

Permission scoping

Nutritionix drives its core lookups through the request body and query, so scope the agent to the operations it needs, such as natural-language nutrient parsing or instant search, and leave the rest out. You choose the operations it may call, so it only reaches the endpoints you list.

Credential isolation

Your Nutritionix x-app-id and x-app-key are stored once, encrypted, by your own Jentic One instance and injected at execution time. They never enter the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'log a meal in natural language' or 'estimate calories burned', and Jentic returns the matching Nutritionix operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using Nutritionix 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 in your Jentic One instance.

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.

Can I limit what my agent is allowed to do with the Nutritionix API?

Yes. Because Jentic One is self-hosted, you set the rules, and only the Nutritionix operations you list are exposed to the agent. You can allow just natural-language nutrient parsing (POST /natural/nutrients) and instant search (GET /search/instant) while leaving out exercise estimation, item and UPC lookup, restaurant locations, or brand details. The agent reaches only the endpoints you permit, and your stored x-app-id and x-app-key are injected at execution time rather than handed to the agent.

Nutritionix API

AI ReadinessAI-Aware (B+)69/100

See full scorecard

Official vendor OpenAPI document · agent-readyData 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.

Use for: I need to log a meal described in plain English and get its calories, Estimate how many calories I burned running for 30 minutes, Search for a branded protein bar in the Nutritionix database, Get the nutrient breakdown for a UPC barcode

Not supported: Does not handle meal-plan generation, grocery delivery, or fitness device sync - use for nutrition lookup and natural-language meal and exercise parsing only.

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.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A+Signals: 4

98%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

100%

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

75%

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: B+Signals: 4

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

75%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

93%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: C-Signals: 4

57%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

50%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1

94%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: C-Signals: 1

50%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

100

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: A+Signals: 1

100%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Nutritionix API to your agent

Capabilities

Start building with Nutritionix API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Nutritionix API

Jentic AI Readiness Score

Nutritionix API

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness