# India Food Label Checker: FSSAI Claims, Sugars, Additives (`anamika67/india-food-label-checker`) Actor

Use when a user asks if a packaged food is healthy or if its label claims are true in India. Finds hidden sugars, decodes INS additives, flags high fat/sugar/salt, and checks 'no added sugar', 'low fat', 'natural' against FSSAI rules, with source.

- **URL**: https://apify.com/anamika67/india-food-label-checker.md
- **Developed by:** [Anamika Singh](https://apify.com/anamika67) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## India Food Label Checker — FSSAI claims, hidden sugars, INS additives

> **Stop your AI from guessing.** AI models guess about food labels, and brands use 10+ names for sugar. This tool returns a sourced, structured answer in seconds.

**Use when:** a user asks if a packaged food is healthy or if its label claims are true in India. Finds hidden sugars, decodes INS additives, flags high fat/sugar/salt, and checks 'no added sugar', 'low fat', 'natural' against FSSAI rules, with source.

For **grocery, diet, fitness, parenting and health-chatbot apps, and fact-check creators**: paste what is printed on a packaged food and get a sourced, factual read-out.

### What you get

- **Hidden sugars**: 30+ names (glucose syrup, invert sugar, malt extract, jaggery, honey…), sugar substitutes (fruit juice concentrate, date paste) and sugar-like carbs (maltodextrin), with their position in the list.
- **Additives decoded**: INS / E numbers → name and function (e.g. 627 → disodium guanylate, flavour enhancer), with factual regulatory notes where they exist.
- **High / medium / low** fat, saturated fat, sugars and salt per 100 g or 100 ml (UK front-of-pack thresholds as reference; India has no final "high in" threshold yet).
- **Claim check against FSSAI (Advertising and Claims) Regulations, 2018**: "low fat", "sugar free", "low sodium", "high fibre", "zero trans fat" (Schedule I limits), "no added sugar" (regulation 6), "natural", "pure", "fresh" (Schedule V). Verdict: `MEETS_CONDITION`, `DOES_NOT_MEET`, `CANNOT_VERIFY`.
- **FSSAI licence number** format check.

### Input

```json
{ "ingredients": "Refined wheat flour (63%), Palm oil, Salt, Flavour enhancers (INS 627, 631), Sugar, Glucose syrup",
  "nutrition": "Per 100 g: Energy 427 kcal, Total Sugars 2.6 g, Total Fat 15.8 g, Saturated Fat 7.3 g, Sodium 1160 mg",
  "claims": ["No added sugar", "Low fat"] }
```

### Output (example)

```json
{ "summary": "2 added sugar source(s); 2 additive(s) identified; high in saturated fat, salt; claim(s) not meeting FSSAI conditions: No added sugar, Low fat.",
  "claims": [{ "claim": "Low fat", "verdict": "DOES_NOT_MEET", "rule": "FSSAI Schedule I: \"low fat\" needs not more than 3 g per 100 g. Label declares 15.8 g." }] }
```

### Honest by design

- Facts against published rules only. **Not medical advice. No judgement of any brand.**
- Every claim verdict quotes the rule and the official FSSAI source.
- Not yet checked: whether each additive is permitted in that specific food category, and protein/vitamin claims (linked to RDA).

### Pricing

Pay per label check. Invalid input is not charged.

# Actor input Schema

## `ingredients` (type: `string`):

Copy the ingredient list exactly, including INS numbers.

## `nutrition` (type: `string`):

e.g. 'Per 100 g: Energy 427 kcal, Total Sugars 2.6 g, Total Fat 15.8 g, Saturated Fat 7.3 g, Sodium 1160 mg'

## `claims` (type: `array`):

e.g. No added sugar, Low fat, Natural, Zero trans fat

## `form` (type: `string`):

Optional; detected from 'per 100 ml'.

## `fssai_number` (type: `string`):

Format check only.

## Actor input object example

```json
{
  "ingredients": "Ingredients: Refined wheat flour (63%), Palm oil, Salt, Thickeners (508, 412), Flavour enhancers (INS 627, 631), Sugar, Maltodextrin, Glucose syrup",
  "nutrition": "Per 100 g: Energy 427 kcal, Protein 9.1 g, Total Sugars 2.6 g, Total Fat 15.8 g, Saturated Fat 7.3 g, Trans Fat 0.1 g, Sodium 1160 mg",
  "claims": [
    "No added sugar",
    "Low fat",
    "Natural"
  ]
}
```

# Actor output Schema

## `results` (type: `string`):

The result.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "ingredients": "Ingredients: Refined wheat flour (63%), Palm oil, Salt, Thickeners (508, 412), Flavour enhancers (INS 627, 631), Sugar, Maltodextrin, Glucose syrup",
    "nutrition": "Per 100 g: Energy 427 kcal, Protein 9.1 g, Total Sugars 2.6 g, Total Fat 15.8 g, Saturated Fat 7.3 g, Trans Fat 0.1 g, Sodium 1160 mg",
    "claims": [
        "No added sugar",
        "Low fat",
        "Natural"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("anamika67/india-food-label-checker").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "ingredients": "Ingredients: Refined wheat flour (63%), Palm oil, Salt, Thickeners (508, 412), Flavour enhancers (INS 627, 631), Sugar, Maltodextrin, Glucose syrup",
    "nutrition": "Per 100 g: Energy 427 kcal, Protein 9.1 g, Total Sugars 2.6 g, Total Fat 15.8 g, Saturated Fat 7.3 g, Trans Fat 0.1 g, Sodium 1160 mg",
    "claims": [
        "No added sugar",
        "Low fat",
        "Natural",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("anamika67/india-food-label-checker").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "ingredients": "Ingredients: Refined wheat flour (63%), Palm oil, Salt, Thickeners (508, 412), Flavour enhancers (INS 627, 631), Sugar, Maltodextrin, Glucose syrup",
  "nutrition": "Per 100 g: Energy 427 kcal, Protein 9.1 g, Total Sugars 2.6 g, Total Fat 15.8 g, Saturated Fat 7.3 g, Trans Fat 0.1 g, Sodium 1160 mg",
  "claims": [
    "No added sugar",
    "Low fat",
    "Natural"
  ]
}' |
apify call anamika67/india-food-label-checker --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,anamika67/india-food-label-checker"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/HJO648hdYafMLjWgD/builds/tbXzg00D3hbgJ1J7d/openapi.json