Install Jentic One Beta

Connect the Noms API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Noms 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%2Fnoms.sh%2Fnoms" | 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%2Fnoms.sh%2Fnoms" | 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 Noms API.

Search foods with typo-tolerant text search through the q parameter on GET /v1/foods

Look up a packaged product by barcode and embed its brand, nutrients, and serving sizes with include

Rank foods by a nutrient's per-100 value, for example sorting by -nutrient[PROTEIN]

Browse the nutrient, brand, and food group reference lists and fetch any single record by id

GET STARTED

Start building with Noms API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Noms API for, with concrete tasks.

★ Nutrition lookup for an AI meal assistant

An AI meal-planning assistant needs real nutrient values instead of guessed ones. Through Jentic the agent searches for 'look up nutrition facts for a food', gets the Noms food search operation with its input schema, and calls it with a q search plus include=nutrients,serving_sizes so the macros and portion weights arrive in one response. The X-API-Key is attached at call time, so the agent works from returned data, not memory.

Call GET /v1/foods with q=greek yogurt and include=nutrients,serving_sizes, then report the protein and energy values per serving for the top match

Barcode scan to nutrient panel

A grocery or fitness app scans a product barcode and needs the matching food record. The Noms barcode filter on GET /v1/foods returns the product, and include=brand,nutrients,images embeds the brand, nutrient values, and product images so the app can render a full nutrition panel from a single call. Decimal values arrive as strings, so the app keeps the published precision.

Call GET /v1/foods with barcode=5000159484695 and include=brand,nutrients,images, then return the brand name and the energy, fat, and sugar values

High-protein food ranking

A diet coach wants a shortlist of foods ordered by a single nutrient. Noms sorts foods by a nutrient's per-100 g or ml value with sort=-nutrient[PROTEIN], and foods that lack the nutrient rank last rather than being dropped. Nutrient codes come from GET /v1/nutrients, so the same pattern works for fibre, iron, or any other listed nutrient.

Call GET /v1/nutrients with q=protein to confirm the nutrient code, then call GET /v1/foods with q=beans and sort=-nutrient[PROTEIN] and list the top results with their protein values

Market and quota housekeeping

On single-market plans, food results are scoped to one country, and an account must pick it before food requests succeed. An integration can read the current selection with GET /v1/market, change it with PUT /v1/market by passing the required market field, and check remaining allowance with GET /v1/usage before starting a batch of lookups.

Call GET /v1/usage to read the remaining quota, then call PUT /v1/market with market set to GB and confirm the new selection in the response

Key Endpoints

11 endpoints — the noms api serves nutritional reference data for foods, brands, nutrients, and food groups over a read-focused rest interface.

METHOD

PATH

DESCRIPTION

GET

/v1/foods

Search and filter foods

GET

/v1/foods/{id}

Get a food

GET

/v1/nutrients

List nutrients

GET

/v1/brands

List brands

GET

/v1/food-groups

List food groups

GET

/v1/usage

Get usage and quota

PUT

/v1/market

Set the market selection

GET

/v1/foods

Search and filter foods

GET

/v1/foods/{id}

Get a food

GET

/v1/nutrients

List nutrients

GET

/v1/brands

List brands

GET

/v1/food-groups

List food groups

GET

/v1/usage

Get usage and quota

PUT

/v1/market

Set the market selection

Why Jentic?

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

Setup

Wiring Noms by hand means sending the X-API-Key header, following links.next for keyset pagination, and handling free-tier 403 rules such as the market selection. Through Jentic you install once, import Noms from the API Directory, store the key once, and your agent calls it.

Permission scoping

Noms reads sit at their own URL paths such as /v1/foods and /v1/nutrients, while the one write, PUT /v1/market, changes the account's market for every key. You choose the operations your agent may call, so that write is not included unless you add it.

Credential isolation

Your Noms API key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'look up nutrition facts for a food' or 'find a product by barcode', and Jentic returns the matching Noms operation with its input schema, including the q, barcode, include, and sort parameters, so the agent calls the right endpoint directly.

FAQs

Specific to using Noms API through Jentic.

What authentication does the Noms API use?

Per its OpenAPI spec, the Noms API authenticates with an API key sent in the X-API-Key header, in the noms_sk_ format, created in the Noms dashboard under API Keys. Through Jentic, the key is held by your own instance and attached to each call, so your agent never sees the raw value.

Can I look up a food by barcode with the Noms API?

Yes. GET /v1/foods accepts a barcode filter, and you can add include=brand,nutrients,serving_sizes to embed the related records in the same response. If you already have the Noms id, GET /v1/foods/{id} returns the single food directly.

What are the rate limits for the Noms API?

The spec describes a per-account request quota set by your plan, shared by every key you own, over a rolling 24-hour window on the free plan and your billing period on paid plans. Responses carry RateLimit-Limit, RateLimit-Remaining, and RateLimit-Reset headers, and GET /v1/usage reports where you stand. Check the Noms pricing page at https://noms.sh for the allowance on each plan.

Why does the Noms API return a 403 on a food search?

On the free tier, list endpoints need a q search rather than a bare or filter-only listing, results are capped in depth, and foods requests fail until a market is selected. Choose the market with PUT /v1/market, keep a q term on list calls, or move to a paid tier, which the spec says lifts all three limits.

How do I get nutrition facts for a food through Jentic?

Search Jentic for 'look up nutrition facts for a food', load the Noms food search operation, and call GET /v1/foods with a q term and include=nutrients,serving_sizes. Your agent reads the per-100 values and portion weights straight from the response. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Is there a Noms MCP server?

You do not need an MCP server to give your agent Noms. Jentic connects it directly from the API Directory: import it, store your API key once, and your agent calls the food, nutrient, and brand operations it needs on demand.

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

Yes. Write a rule that allows the food, nutrient, brand, and food group read operations plus GET /v1/usage, and the agent can search and read nutrition data without being able to call PUT /v1/market. Its calls are logged, so you can review what it looked up.

Noms Sh Noms API

AI ReadinessAI-Ready (A-)76/100

See full scorecard

Official vendor OpenAPI document · agent-readyData EnrichmentData TransformationapiKey11 EndpointsREST

For Agents

Search foods by name or barcode, read per-100 g nutrient values, and look up brands, nutrients, and food groups from the Noms nutrition database.

Use for: Find the nutrition facts for a food by name, Look up a packaged product by its barcode, List the foods with the most protein per 100 grams, Get the serving sizes for a specific food

Not supported: Does not handle recipe search, meal logging, diet tracking, or grocery ordering. Use for looking up food, brand, and nutrient reference data only.

The Noms API serves nutritional reference data for foods, brands, nutrients, and food groups over a read-focused REST interface. A client can search foods with typo-tolerant text search, look a product up by barcode, filter by brand or food group, and sort results by a nutrient's per-100 g or ml value. Food records can embed their brand, food group, nutrients, serving sizes, images, and market countries in one response, and decimals arrive as strings to keep full precision. Account endpoints report request usage and set the market (country) that food results are scoped to.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A+Signals: 4

96%

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).

100%

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: A-Signals: 4

15%

Example Density

How richly the API is illustrated with examples.

99%

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).

100%

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: B+Signals: 4

56%

Description Coverage

Coverage of descriptions across API elements.

100%

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

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

12%

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).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: A+Signals: 1

98%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Noms API to your agent

Capabilities

Start building with Noms API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Noms Sh Noms API

Jentic AI Readiness Score

Noms 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