# Japan Chain Restaurant Nutrition & Allergen Data (Tabecal) (`tabecal/tabecal-japan-restaurant-nutrition`) Actor

Official nutrition facts (kcal, protein, fat, carbs, salt), prices, allergens, menu-change history and store locations for ~78 Japanese restaurant / fast-food / convenience-store chains and ~19,000 menu items. Updated daily from official sources. Works with AI agents via Apify MCP.

- **URL**: https://apify.com/tabecal/tabecal-japan-restaurant-nutrition.md
- **Developed by:** [Tabecal](https://apify.com/tabecal) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.20 / 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

## Japan Chain Restaurant Nutrition & Allergen Data (Tabecal)

Official nutrition facts for **~78 Japanese restaurant, fast-food and convenience-store chains — ~19,000 menu items** — straight from each chain's published tables, refreshed daily, with version history.

Use it to answer questions like *"gyudon under 600 kcal with 20 g+ protein"*, *"does this CoCo Ichibanya curry contain egg?"*, *"which Starbucks drinks changed this month?"*, or *"McDonald's stores within 1 km of Tokyo Station"* — from an app, a spreadsheet, or an AI agent (this Actor works with **Apify MCP**, so Claude / ChatGPT / Cursor can call it as a tool).

### What you get

| Field | Meaning |
|---|---|
| `kcal`, `protein_g`, `fat_g`, `carb_g`, `fiber_g`, `sugar_g` | Energy and macronutrients as published |
| `salt_g` | Salt equivalent (食塩相当量), `sodium_mg` where published |
| `price` | JPY, tax included (6 chains publish prices) |
| `item_key` | Permanent id of item × size, for `item_detail` / `allergen_lookup` |
| `valid_from` | First day the current values were confirmed |

`null` = the chain does not publish that field (no estimates are ever filled in).

Coverage: Yoshinoya, Sukiya, Matsuya, McDonald's, Mos Burger, KFC, Starbucks, Doutor, Komeda, Saizeriya, Gusto, Denny's, Royal Host, Sushiro, Kura Sushi, Hama Sushi, CoCo Ichibanya, Ootoya, Yayoiken, Marugame Seimen, 7-Eleven, FamilyMart, Lawson, nosh and more (run `list_chains`). Allergen tables (28 Japanese labelling allergens) for 38 chains. 28,000+ store locations (OpenStreetMap).

### Operations

| `operation` | Returns |
|---|---|
| `search_items` | Items matching words + nutrition limits (`kcalMax`, `proteinMin`, `saltMax`, `allergenFree` …), sorted (`sort`) |
| `chain_items` | Every current item of one chain |
| `list_chains` / `chain_overview` | Covered chains with coverage stats / one chain's categories and recent changes |
| `item_detail` | One item with version history, change events, allergens, sales attributes |
| `recent_changes` | New / discontinued / changed items since a date |
| `allergen_lookup` | Allergen statement for one item grouped as contains / may\_contain / none |
| `stores_nearby` | Stores near lat/lon (sorted by distance) or by prefecture |

#### Example input

```json
{ "operation": "search_items", "query": "牛丼", "kcalMax": 600, "proteinMin": 20, "sort": "protein", "maxResults": 50 }
```

```json
{ "operation": "allergen_lookup", "chain": "cocoichibanya", "itemName": "ポークカレー" }
```

#### Example output row

```json
{ "item_key": "5a1c0e9d2b7f4a10", "chain": "吉野家", "chain_slug": "yoshinoya", "name": "牛丼", "size": "並盛", "kcal": 635, "protein_g": 20.0, "fat_g": 23.4, "carb_g": 89.0, "salt_g": 2.7, "price": null, "valid_from": "2026-08-16", "source": "tabecal.com" }
```

### Pricing

Pay per event: a small fee per run plus a fee per returned row (see the Pricing tab). No subscription. Need thousands of calls a day or a full data dump (CSV / JSON / SQLite with full history)? Use the API directly: <https://tabecal.com/api/>.

### Terms & attribution

- Values are the chains' own published figures. Verify with the chain before any medical or allergy decision.
- Display inside your app is fine; redistributing the data itself (dumps, re-selling as an API) is not.
- Please credit **"Data: Tabecal (tabecal.com) / official published values"**. Store coordinates © OpenStreetMap contributors (ODbL).
- Chain names and trademarks belong to their owners; Tabecal is not affiliated with any chain.

# Actor input Schema

## `operation` (type: `string`):

What to fetch.

## `query` (type: `string`):

Japanese words matched against item name / category (space = AND). e.g. 牛丼

## `chain` (type: `string`):

Chain slug (yoshinoya, mcdonalds, starbucks …) or Japanese name. Run list\_chains to see all 78.

## `genre` (type: `string`):

burger, cafe, conveni, curry, family, gyudon, health, izakaya, noodle, pizza, sushi, sweets, teishoku, yakiniku

## `category` (type: `string`):

Official menu category (partial match), e.g. 定食

## `kcalMin` (type: `integer`):

Minimum calories (kcal) per serving.

## `kcalMax` (type: `integer`):

Maximum calories (kcal) per serving.

## `proteinMin` (type: `integer`):

Minimum protein (g) per serving.

## `fatMax` (type: `integer`):

Maximum fat (g) per serving.

## `carbMax` (type: `integer`):

Maximum carbohydrate (g) per serving.

## `sugarMax` (type: `integer`):

Maximum sugar / available carbohydrate (g) per serving (only chains that publish it).

## `saltMax` (type: `number`):

Maximum salt equivalent (g) per serving.

## `priceMax` (type: `integer`):

Maximum price in JPY (only chains that publish prices).

## `allergenFree` (type: `array`):

Items published as containing / possibly containing these are excluded. Use Japanese labels: 卵 乳 小麦 そば 落花生 えび かに くるみ あわび いか いくら オレンジ カシューナッツ キウイフルーツ 牛肉 ごま さけ さば 大豆 鶏肉 バナナ 豚肉 マカダミアナッツ もも やまいも りんご ゼラチン アーモンド 魚介類

## `knownAllergensOnly` (type: `boolean`):

With 'Exclude allergens': keep only items whose chain publishes allergen tables and lists the allergen as 'none'.

## `sort` (type: `string`):

Sort order of results (e.g. kcal, -kcal, protein, -protein, salt, price).

## `itemKey` (type: `string`):

For item\_detail / allergen\_lookup: 16-hex key from search results

## `itemName` (type: `string`):

For allergen\_lookup when the key is unknown (with Chain)

## `since` (type: `string`):

For recent\_changes. Default: 30 days ago

## `event` (type: `string`):

Change event type filter: added, removed or changed.

## `lat` (type: `number`):

For stores\_nearby

## `lon` (type: `number`):

Longitude for nearby store search (use with lat).

## `radiusKm` (type: `number`):

Search radius in km for nearby store search (default 2).

## `pref` (type: `string`):

For stores\_nearby without coordinates, e.g. 東京都

## `maxResults` (type: `integer`):

Up to 1000 (pages automatically).

## Actor input object example

```json
{
  "operation": "search_items",
  "query": "牛丼",
  "kcalMax": 600,
  "knownAllergensOnly": false,
  "sort": "name",
  "radiusKm": 3,
  "maxResults": 100
}
```

# Actor output Schema

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

Menu items / allergens / changes / stores as JSON rows. Each row includes chain, name, size, kcal, protein\_g, fat\_g, carb\_g, salt\_g, price, item\_key.

## `resultsCsv` (type: `string`):

No description

# 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 = {
    "operation": "search_items",
    "query": "牛丼",
    "kcalMax": 600
};

// Run the Actor and wait for it to finish
const run = await client.actor("tabecal/tabecal-japan-restaurant-nutrition").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 = {
    "operation": "search_items",
    "query": "牛丼",
    "kcalMax": 600,
}

# Run the Actor and wait for it to finish
run = client.actor("tabecal/tabecal-japan-restaurant-nutrition").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 '{
  "operation": "search_items",
  "query": "牛丼",
  "kcalMax": 600
}' |
apify call tabecal/tabecal-japan-restaurant-nutrition --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,tabecal/tabecal-japan-restaurant-nutrition"
        }
    }
}
```

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/TGHBdmmWzvo0D9eb6/builds/jTY3x3qFjFJMxCt6i/openapi.json