# Zomato Restaurants Scraper (`parseforge/zomato-restaurants-scraper`) Actor

Scrapes restaurant listings from Zomato city pages. Returns each restaurant as a flat row with name, cuisine, rating, cost for two, and location. Supports multiple city URLs and proxy rotation.

- **URL**: https://apify.com/parseforge/zomato-restaurants-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** Business
- **Stats:** 2 total users, 1 monthly users, 75.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.43 / 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/platform/actors/running/actors-in-store#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

[![ParseForge](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg)](https://apify.com/parseforge?fpr=vmoqkp)

### Zomato Restaurants Scraper

**Scrape restaurant listings from any Zomato city page, up to hundreds per run.** Every restaurant comes with its name, cuisine, rating, cost for two, and location. No API key required. Export to CSV, JSON, Excel, or XML.

Zomato's official API is restricted to registered partners and does not serve public restaurant listing data for bulk analysis. This actor reads the public city listing pages directly, so you can collect restaurant profiles from Delhi, Mumbai, Bangalore, or any Zomato city URL. It returns each restaurant as one flat row, ready for market research, competitor tracking, or lead generation.

| Who uses it | What they scrape Zomato for |
|---|---|
| Market researchers | Map the restaurant density and cuisine mix in a target city. |
| Food delivery startups | Build a prospecting list of restaurants not yet on their platform. |
| Restaurant tech vendors | Find restaurants by area and rating for POS or SaaS outreach. |
| Data analysts | Track rating trends and pricing across neighborhoods over time. |

### What it does

This Actor collects restaurant listings from Zomato city pages and returns each restaurant as a structured row with its name, cuisine, rating, cost for two, and location.

- 📍 **City-level scraping:** feed one or more Zomato city listing URLs and collect every restaurant on each page.
- 🔢 **Max items control:** set a hard limit on the number of restaurants extracted per run to stay within your budget.
- 🛡️ **Proxy rotation:** built-in Apify proxy support keeps your requests distributed and reduces blocking.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

### What you can do with Zomato data

**📊 Market sizing and cuisine analysis.**

A restaurant-tech analyst scrapes all Bangalore listings to count restaurants by cuisine and average cost for two, then sizes the addressable market for a new B2B product.

**📋 Lead list generation.**

A food-delivery sales team scrapes Mumbai restaurants rated above 4.0 and exports the list to their CRM for direct outreach.

**📍 Location intelligence.**

A real-estate consultant scrapes multiple Delhi neighborhoods to map restaurant clusters and advise a client on the best high-street location for a new cafe.

**📈 Competitor price tracking.**

A restaurant owner scrapes their city page weekly, filters by their own cuisine, and tracks how competitors adjust their cost-for-two over a quarter.

### Why choose this scraper

| | What you get |
|---|---|
| **No API registration** | Reads public Zomato pages, so you skip OAuth and rate-limit negotiations. |
| **Fixed flat schema** | Every restaurant lands as one row with the same columns, ready for analysis. |
| **Multi-city runs** | Queue several city URLs in one run and get a combined dataset. |

### How it compares

This actor focuses on restaurant listing data from city pages, while the Zomato Restaurant Reviews Scraper targets individual review-level data from restaurant profile pages.

| Feature | ParseForge | Zomato Restaurant Reviews Scraper 🍽️ |
|---|---|---|
| Scrapes city listing pages | Yes | Not listed |
| Extracts restaurant name and cuisine | Yes | Not listed |
| Extracts cost for two | Yes | Not listed |
| Extracts user reviews and review text | Not listed | Yes |
| Multi-URL input support | Yes | Not listed |

### Configure the run

Drive the Actor from one or more Zomato city listing URLs, and set a maximum item count so only the top N restaurants reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

```json
{
 "startUrls": [
 {
 "url": "https://www.zomato.com/bangalore/restaurants"
 }
 ],
 "proxyConfiguration": {
 "useApifyProxy": true
 }
}
```

A larger pull:

```json
{
 "startUrls": [
 {
 "url": "https://www.zomato.com/bangalore/restaurants"
 }
 ],
 "proxyConfiguration": {
 "useApifyProxy": true
 },
 "maxItems": 200
}
```

### Pricing

Pay-per-result: **$0.00269 per result** collected. You pay only for the results written to your dataset.

| Results collected | Approximate cost |
|---|---|
| 100 results | $0.27 |
| 1,000 results | $2.69 |
| 10,000 results | $26.90 |

New Apify accounts start with $5 in free credit.

### Free users

Free-plan runs return up to 10 results as a preview. [Upgrade your Apify plan](https://console.apify.com/sign-up?fpr=vmoqkp) to collect up to 1,000,000 results per run.

### Run it

1. [Create a free Apify account with $5 in credit](https://console.apify.com/sign-up?fpr=vmoqkp).
2. Open the [Zomato Restaurants Scraper](https://apify.com/parseforge/zomato-restaurants-scraper?fpr=vmoqkp).
3. Set your inputs and any filters, then click **Start**.
4. Export the results as CSV, Excel, JSON, or XML from the **Dataset** tab.

Run it programmatically through the [Apify API](https://docs.apify.com/api/v2) (`run-sync-get-dataset-items`) or the [ApifyClient](https://docs.apify.com/api/client/js) for JavaScript and Python.

### Use with AI agents (MCP)

Give an AI agent live access to Zomato through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

```bash
claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/zomato-restaurants-scraper"
```

Then prompt it in plain language to run the scraper and read back the results.

### Troubleshooting

**Why am I getting no results?**

Check that your start URL is a valid Zomato city listing page and that the page loads in a regular browser. Also verify that your max items is set to a number greater than zero.

**The actor returns fewer items than my max items setting.**

The city page may have fewer total listings than your limit, or some listings may have been filtered out by Zomato. Try a broader city URL or a different location.

**I am getting blocked or seeing captchas.**

Enable the proxy configuration and select Apify Proxy. For very large runs, reduce the max items per run and split the work across multiple runs with different city URLs.

**Some restaurant fields are empty in my dataset.**

Zomato listings sometimes omit fields like cost for two or rating for newer or unclaimed restaurants. The actor returns whatever is publicly visible on the listing page.

**The run takes a long time.**

Large max items values mean more pages to load. Lower the max items or split your target cities into separate, smaller runs that can execute in parallel.

### FAQ

| Question | Answer |
|---|---|
| Can I scrape a specific cuisine or only whole city pages? | The actor starts from the city listing URLs you provide. If Zomato offers a filtered URL for a cuisine, you can use that as a start URL. The actor does not apply its own cuisine filter. |
| How many restaurants can I scrape in one run? | You set the maximum with the 'Max items' field. The actor stops when it reaches that count or when the city page runs out of listings, whichever comes first. |
| Does this scrape restaurant menus or reviews? | No, this actor collects the listing-level data you see on a city page: name, cuisine, rating, cost for two, and location. It does not open individual restaurant pages for menus or reviews. |
| Which cities are supported? | Any city that has a Zomato listing page. Provide the URL, and the actor will scrape it. Common examples include Delhi NCR, Mumbai, Bangalore, Pune, Hyderabad, and Chennai. |
| Do I need a Zomato account or API key? | No. The actor reads the public pages that anyone can visit in a browser. No login, no API key, no OAuth. |
| What output formats can I get? | You can export your dataset as CSV, JSON, Excel, or XML directly from the Apify platform. |
| Will I get blocked by Zomato? | The actor uses Apify proxy rotation to distribute requests. For large runs, we recommend setting a reasonable max items count and using the proxy configuration to reduce the chance of blocking. |
| Can I schedule this to run daily? | Yes. Once you have configured the actor, you can set a schedule in Apify to run it every day, week, or any interval you need. |
| Does the actor handle infinite scrolling on Zomato? | Yes, the actor navigates the listing pages to collect restaurants beyond the first page, up to your max items limit. |

### Related actors

Browse the full [ParseForge collection](https://apify.com/parseforge?fpr=vmoqkp) for more scrapers.

🆘 **Need help?** Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ **Disclaimer.** This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Zomato Ltd. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.

# Actor input Schema

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

List of Zomato restaurant listing pages to scrape.

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

Maximum number of restaurants to extract.

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

Select proxies to avoid blocking.

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://www.zomato.com/bangalore/restaurants"
    }
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

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

Complete dataset of all scraped 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": [
        {
            "url": "https://www.zomato.com/bangalore/restaurants"
        }
    ],
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/zomato-restaurants-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": [{ "url": "https://www.zomato.com/bangalore/restaurants" }],
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("parseforge/zomato-restaurants-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": [
    {
      "url": "https://www.zomato.com/bangalore/restaurants"
    }
  ],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call parseforge/zomato-restaurants-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,parseforge/zomato-restaurants-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/AgDLjDtHEEJQBkA8z/builds/sINPS8XGWEb81QDFq/openapi.json