# Zomato Restaurant Reviews Scraper (`bovi/zomato-scraper`) Actor

Collect public Zomato restaurant profile data and logged-out restaurant reviews as structured dataset records.

- **URL**: https://apify.com/bovi/zomato-scraper.md
- **Developed by:** [Vitalii Bondarev](https://apify.com/bovi) (community)
- **Categories:** E-commerce, Lead generation, Marketing
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.20 / 1,000 zomato restaurant reviews scrapers

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

## Zomato Restaurant Reviews Scraper

Collect public restaurant profile details and reviews from Zomato. Provide one or more restaurant page or review URLs. The default dataset contains review records with the rating, experience type, review text, relative timestamp, reviewer profile, comment counts, and a nested copy of the restaurant profile when those values are present on the page. The actor also writes each restaurant profile once to a separate `restaurants` dataset. It reads the public first five review pages for each restaurant and does not log in.

### Input

| Field | Type | Description | Default |
| --- | --- | --- | --- |
| `startUrls` | array of strings | Zomato restaurant URLs. A restaurant page URL is accepted; the actor opens its reviews page. | A public Mumbai restaurant review page |
| `maxResults` | integer | Maximum number of review records in the default dataset. Restaurant profile rows are written once to the separate `restaurants` dataset. | `50` |
| `proxyConfiguration` | object | Optional Apify Proxy settings. Omit or disable it to use a direct connection. | No proxy |

The default dataset has one review per row. Each row contains the restaurant ID, name, and URL, the review ID, rating, review type, text, relative time, reviewer name and public profile URL, review link, and comment counts when present. Its nested `restaurant` object carries the profile's public phone numbers, address, city, postal code, coordinates, cuisines, aggregate rating, rating count, and opening-hours text. The separate `restaurants` dataset has one profile row per restaurant. Values that are not present on the page are omitted.

### Example output

```json
{
  "recordType": "review",
  "restaurantId": "35226",
  "restaurantName": "Lucky Restaurant - Since 1938",
  "reviewId": "509493952",
  "rating": 5,
  "ratingType": "DINING",
  "reviewText": "Very good",
  "timestamp": "one month ago",
  "commentCount": 0,
  "restaurant": {
    "city": "Mumbai",
    "latitude": 19.1734664,
    "longitude": 72.8511448
  }
}
```

### Price per result

The reference Free-plan rate is **$0.005 per dataset item**; rates can be lower on paid plans. Check this actor's Apify Store Pricing tab for the current rate. Apify bills items pushed to the dataset automatically. This actor does not add an `Actor.charge` fee.

### Limits

Zomato's logged-out pages expose a limited recent review window. The actor stops after the first five review pages for each restaurant and returns only data present in those public pages. A URL that requires login or cannot be fetched produces no fabricated records; inaccessible pages are reported in the actor log.

# Actor input Schema

## `startUrls` (type: `array`):

Enter Zomato restaurant page or review URLs. The actor opens the public reviews page for each restaurant and reads up to five pages.

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

Maximum number of review records to write to the default dataset. Restaurant profiles are written once to the restaurants dataset.

## `proxyConfiguration` (type: `object`):

Optional Apify Proxy settings. If omitted or disabled, requests use the direct connection.

## Actor input object example

```json
{
  "startUrls": [
    "https://www.zomato.com/mumbai/lucky-restaurant-since-1938-goregaon-east/reviews"
  ],
  "maxResults": 50,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

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

Dataset with the scraped restaurant and review records.

# 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 = {
    "startUrls": [
        "https://www.zomato.com/mumbai/lucky-restaurant-since-1938-goregaon-east/reviews"
    ],
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("bovi/zomato-scraper").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 = {
    "startUrls": ["https://www.zomato.com/mumbai/lucky-restaurant-since-1938-goregaon-east/reviews"],
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("bovi/zomato-scraper").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 '{
  "startUrls": [
    "https://www.zomato.com/mumbai/lucky-restaurant-since-1938-goregaon-east/reviews"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call bovi/zomato-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bovi/zomato-scraper"
        }
    }
}
```

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/MxjDzEmyIg0RIT7W7/builds/1RITfNYKzlpo1zjHg/openapi.json