# Restaurant Menu & Price Intelligence (`azzarilabs/restaurant-menu-price-intelligence`) Actor

Global restaurant menu extraction, competitor price comparison, monitoring, chain intelligence, and delivery price intelligence.

- **URL**: https://apify.com/azzarilabs/restaurant-menu-price-intelligence.md
- **Developed by:** [Azzari Labs](https://apify.com/azzarilabs) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$9.00 / 1,000 successful restaurant menu analyses

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Global Restaurant Menu & Price Intelligence

Public facade deployment candidate for `azzarilabs/restaurant-menu-price-intelligence`.

The facade exposes the global V1 input contract with `extract`, `compare`, `monitor`, and `chain`. It securely delegates the sanitized public input to the pinned private Core, then copies the Core Dataset, `OUTPUT`, and `REPORT.html` into the public run. Extraction, normalization, adapters, snapshots, deltas, intelligence, and reporting remain exclusively in the Core.

### Required environment

- `ACTOR3_CORE_ACTOR_ID=azzarilabs/restaurant-menu-price-intelligence-core`
- `ACTOR3_CORE_BUILD=<immutable validated build number or isolated build tag>`
- `APIFY_TOKEN=<secret>` — injected and stored as a secret by Apify; never include it in Actor input or source.

`ACTOR3_CORE_BUILD=latest` is rejected. The calling token must have permission to run the private Core and read its run storages.

No paid API, paid AI, purchased proxy, OCR, currency conversion, automatic restaurant search, or delivery-platform bypass is added by this facade.

# Actor input Schema

## `urls` (type: `array`):

Entre 1 y 20 URLs públicas de restaurantes o canales delivery de cualquier país. No restringe dominios por geografía ni realiza búsqueda automática.

## `mode` (type: `string`):

extract: extracción; compare: competidores; monitor: cambios históricos; chain: ubicaciones de una cadena.

## `language` (type: `string`):

Idioma de las etiquetas generadas en REPORT.html; los datos fuente no se traducen.

## `currency_override` (type: `string`):

Código ISO 4217, por ejemplo USD o MXN. Si se omite y la moneda es ambigua, se devuelve null.

## Actor input object example

```json
{
  "urls": [
    "https://roasteryhouse.com/"
  ],
  "mode": "extract",
  "language": "es"
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `output` (type: `string`):

No description

## `report` (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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("azzarilabs/restaurant-menu-price-intelligence").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("azzarilabs/restaurant-menu-price-intelligence").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 '{}' |
apify call azzarilabs/restaurant-menu-price-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,azzarilabs/restaurant-menu-price-intelligence"
        }
    }
}

```

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/V69wQvvbJFlur0BmB/builds/rkLh4HEOfmFoVLTGM/openapi.json