# Zomato Scraper — 11 Fields, Any India City, No Login (`themineworks/zomato-scraper`) Actor

Scrape Zomato restaurant listings by city and cuisine: name, locality, address, cuisines, dining and delivery ratings, cost for two, photo. India restaurant data and lead generation at scale. No login, residential proxy. Works in Claude, ChatGPT and any MCP agent.

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

## Pricing

from $1.80 / 1,000 restaurants

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

## Zomato Restaurant Scraper — Ratings, Cuisine, No Login

Extract restaurant listings from **Zomato** by **city + cuisine**. Get restaurant **names, localities, addresses, cuisine tags, dining and delivery ratings, cost for two, and photos** — structured, deduplicated, and ready for market research, competitive analysis, or restaurant lead generation.

> ⚡ Part of a **69-scraper suite** trusted by **450+ developers** across **8,000+ runs** · **>99% run success** · **no login, no cookies, no ban risk**.

> 💸 **You're only charged for delivered results.** Empty searches, failed pages and duplicate listings are never billed.

### Why this scraper

Most Zomato scrapers force you onto slow, expensive residential proxies. This actor was **measured to return identical results on datacenter proxy** — same restaurants, same field fill rates, faster and cheaper. If page 1 is ever blocked it **retries once on Indian residential automatically**, so you only pay residential rates on the rare run that actually needs them.

### Output fields

| Field | Description |
|---|---|
| `name` | Restaurant name |
| `city` | City searched |
| `locality` | Locality / neighbourhood within the city |
| `address` | Full address string |
| `cuisines` | List of cuisine tags |
| `rating_dining` | Zomato dining rating (out of 5) |
| `rating_delivery` | Zomato delivery rating (out of 5) |
| `cost_for_two` | Approximate cost for two, in INR |
| `restaurant_url` | Zomato restaurant page URL |
| `image_url` | Featured photo URL |
| `scraped_at` | ISO-8601 timestamp of the scrape |

### Input

| Field | Description | Example |
|---|---|---|
| `city` | Indian city | `Mumbai`, `Bangalore`, `Hyderabad` |
| `searchQuery` | Cuisine / dish (optional) | `Korean`, `Biryani`, `Desserts` |
| `maxResults` | Max restaurants (1–300) | `30` |
| `proxyConfiguration` | Proxy — datacenter default, auto-retries residential | — |

```json
{
  "city": "Bangalore",
  "searchQuery": "Korean",
  "maxResults": 30,
  "proxyConfiguration": { "useApifyProxy": true }
}
```

### Output sample

```json
{
  "name": "Seoul Kitchen",
  "city": "Bangalore",
  "locality": "Indiranagar",
  "address": "100 Feet Road, Indiranagar, Bangalore",
  "cuisines": ["Korean", "Asian", "BBQ"],
  "rating_dining": 4.4,
  "rating_delivery": 4.1,
  "cost_for_two": 1400,
  "restaurant_url": "https://www.zomato.com/bangalore/seoul-kitchen-indiranagar",
  "image_url": "https://b.zmtcdn.com/data/pictures/...jpg",
  "scraped_at": "2026-07-25T09:30:00Z"
}
```

### Use cases

- **Market research** — map cuisine coverage, pricing tiers and rating distributions across cities.
- **Competitive analysis** — track competitor restaurants' ratings, delivery scores and cost positioning.
- **Restaurant lead generation** — build outreach lists for suppliers, aggregators and delivery services.
- **Location scouting** — find under-served cuisines and price points by locality.

### Run it from Python

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("themineworks/zomato-scraper").call(run_input={
    "city": "Hyderabad",
    "searchQuery": "Biryani",
    "maxResults": 50,
    "proxyConfiguration": {"useApifyProxy": True},
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row["name"], row["locality"], row["rating_dining"], row["cost_for_two"])
```

### FAQ

**Do I need a Zomato login or API key?**
No. The actor runs without any login, password or cookies.

**Do I have to pay for residential proxy?**
No. It runs on datacenter proxy by default (measured to match residential on this target) and only escalates to Indian residential on the rare blocked run.

**Can I get delivery vs dining ratings separately?**
Yes — `rating_dining` and `rating_delivery` are returned as separate fields.

**Will I be charged for empty or failed runs?**
No. You pay only for delivered restaurant records.

***

Part of the [themineworks scraper suite](https://apify.com/themineworks) — JustDial, IndiaMART, Naukri, AmbitionBox, Trustpilot and more India-focused data actors.

# Actor input Schema

## `city` (type: `string`):

Indian city to search restaurants in (e.g. Mumbai, Delhi, Bangalore, Hyderabad, Pune, Chennai).

## `searchQuery` (type: `string`):

Optional cuisine or dish to filter by (e.g. Korean, Pizza, Biryani, Chinese, Desserts). Leave empty to list all restaurants in the city.

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

Maximum number of restaurants to return.

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

Apify Proxy. Defaults to datacenter, measured to return identical results to an Indian residential proxy on this target — same restaurants, same field fill rates, and faster. Note datacenter has no Indian exit nodes, so no country is pinned; Zomato does not require one. If page 1 is blocked the actor retries once on Indian residential automatically, so you only pay residential rates when they are actually needed. Set a group explicitly here to override that behaviour.

## Actor input object example

```json
{
  "city": "Mumbai",
  "maxResults": 5,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `results` (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 = {
    "city": "Mumbai",
    "maxResults": 5,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("themineworks/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 = {
    "city": "Mumbai",
    "maxResults": 5,
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("themineworks/zomato-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "city": "Mumbai",
  "maxResults": 5,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call themineworks/zomato-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=themineworks/zomato-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/R29JeCVz77qaYyPOA/builds/raEJTTkuseaJ0SRML/openapi.json