# Restaurant Menu Extractor – Items, Prices and Sections (`signal_lab/restaurant-menu-extractor`) Actor

Extract restaurant menu items, sections, descriptions, prices, currencies, diets, and nutrition from JSON-LD or configurable CSS selectors.

- **URL**: https://apify.com/signal\_lab/restaurant-menu-extractor.md
- **Developed by:** [Signal Lab](https://apify.com/signal_lab) (community)
- **Categories:** Business, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.70 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## Restaurant Menu Extractor – Items, Prices and Sections

Convert public restaurant menu pages into clean item, section, description, price, currency, and dietary-detail records for catalogs, price analysis, and monitoring.

### Run a verified example

[Extract a restaurant menu with prices](https://apify.com/signal_lab/restaurant-menu-extractor/examples/extract-a-restaurant-menu-with-prices) opens a ready-to-run public task with a small verified sample.

### What you can do

- Build structured menu catalogs from public pages.
- Compare restaurant pricing across datasets.
- Capture menu sections, item descriptions, currency, and dietary details.
- Schedule repeated runs and compare outputs downstream.

### Start quickly

Structured schema.org menus work automatically. For compatible custom pages, add selectors for the item container, name, price, and description.

```json
{
  "urls": [
    "https://signal-lab-tools.vitaxastar.chatgpt.site/fixtures/restaurant-menu"
  ],
  "maxItems": 10
}
```

1. Add public restaurant or menu pages to `urls`.
2. Run the small built-in sample.
3. If no items are found, add the optional CSS selectors.
4. Export the resulting menu-item rows or save the input as a scheduled task.

### Output

Each successful row can include restaurant, menu section, item name, description, normalized price and currency, dietary details, nutrition, source URL, extraction method, and scrape time.

### Troubleshooting

- **No items:** provide selectors for a repeated menu-item container and its fields.
- **Price missing:** confirm the price is visible as text or structured metadata.
- **Currency missing:** include the currency in the selected price text or use a source that exposes `priceCurrency`.
- **PDF or image menu:** this Actor targets HTML pages and does not perform OCR.

### Free workflow guide

See the [restaurant menu data workflow, sample input, output fields, and FAQ](https://signal-lab-tools.vitaxastar.chatgpt.site/workflows/restaurant-menu-data).

### Pricing and responsible use

Base pricing is **$1.00 per 1,000 successful menu-item rows** plus the small start event. Eligible Store discounts can reduce the displayed starting price to **$0.70 per 1,000 rows**; the Pricing tab shows the exact price for your plan before you run. You pay only for rows actually produced. Use public data responsibly and follow the source site’s terms.

# Actor input Schema

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

Public restaurant and menu pages.

## `itemSelector` (type: `string`):

Optional CSS selector for each menu item container.

## `nameSelector` (type: `string`):

Optional selector relative to each item.

## `priceSelector` (type: `string`):

Optional selector relative to each item.

## `descriptionSelector` (type: `string`):

Optional selector relative to each item.

## `maxItems` (type: `integer`):

Hard cap for emitted dataset rows and pay-per-event charges.

## Actor input object example

```json
{
  "urls": [
    "https://signal-lab-tools.vitaxastar.chatgpt.site/fixtures/restaurant-menu"
  ],
  "maxItems": 10
}
```

# Actor output Schema

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

No description

## `summary` (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 = {
    "urls": [
        "https://signal-lab-tools.vitaxastar.chatgpt.site/fixtures/restaurant-menu"
    ],
    "maxItems": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("signal_lab/restaurant-menu-extractor").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 = {
    "urls": ["https://signal-lab-tools.vitaxastar.chatgpt.site/fixtures/restaurant-menu"],
    "maxItems": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("signal_lab/restaurant-menu-extractor").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 '{
  "urls": [
    "https://signal-lab-tools.vitaxastar.chatgpt.site/fixtures/restaurant-menu"
  ],
  "maxItems": 10
}' |
apify call signal_lab/restaurant-menu-extractor --silent --output-dataset

```

## MCP server setup

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

```

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/FYkfmMyrDNKYZIbeE/builds/Y5v9ZjGhAdWDyBSvG/openapi.json