# Swiggy Scraper: Restaurants, Ratings & Cuisines (`themineworks/swiggy-scraper`) Actor

Scrape Swiggy restaurant listings by Indian city — name, rating, cuisines, cost for two, delivery time, offers and locality. No login, pay per restaurant. Food-delivery market research and competitor tracking. Use it as an MCP server in Claude, ChatGPT & AI agents.

- **URL**: https://apify.com/themineworks/swiggy-scraper.md
- **Developed by:** [The Mine Works](https://apify.com/themineworks) (community)
- **Categories:** E-commerce, MCP servers
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.50 / 1,000 restaurant scrapeds

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

## Swiggy Scraper: Restaurants, Ratings & Cuisines

Scrape Swiggy restaurant listings by Indian city — name, rating, cuisines, cost for two, delivery time, offers and locality. No login, pay per restaurant. Food-delivery market research and competitor tracking. Use it as an MCP server in Claude, ChatGPT & AI agents.

> ⚡ Part of a 74-scraper suite with 8,800+ runs · no login, no cookies, no ban risk.
>
> 💸 You are only charged for delivered results — empty searches, failed pages and duplicates are never billed.

### What it does

Swiggy is India's largest food-delivery platform. Its restaurant listings are geo-indexed —
what you see depends on the coordinates you ask from — so a single request only ever returns the
handful of restaurants serving one point.

This actor handles that properly: it samples several coordinates across a city and merges the
results, deduplicating by restaurant id, so you get genuine city-level coverage instead of one
neighbourhood. Each record carries the restaurant id and name, city, area and locality, cuisines
array, rating and rating count, cost for two, delivery time in minutes, distance, any active offer
and a canonical URL.

### Input

| Field | Type | Required | Default | Description |
|---|---|---|---|---|
| `city` | string | no | `"bangalore"` | Indian city to scrape. |
| `latitude` | string | no | — | Override the city centroid with an exact latitude. |
| `longitude` | string | no | — | Override the city centroid with an exact longitude. |
| `maxResults` | integer | no | `10` | Maximum restaurants to return. |

#### Example input

```json
{
  "city": "bangalore",
  "maxResults": 10
}
```

### Output

One record per restaurant. Field list and example below are taken from a real run, not a mock-up.

| Field | Type | Example |
|---|---|---|
| `restaurant_id` | string | `"10575"` |
| `name` | string | `"Pizza Hut"` |
| `city` | string | `"bangalore"` |
| `area` | string | `"Central Bangalore"` |
| `locality` | string | `"Richmond Town"` |
| `cuisines` | array | `["Pizzas"]` |
| `rating` | number | `4.3` |
| `rating_count` | string | `"12K+"` |
| `cost_for_two` | string | `"₹600 for two"` |
| `delivery_time_mins` | number | `27` |
| `distance` | string | `"2.7 km"` |
| `offer` | string | `"ITEMS"` |
| `image_id` | string | `"RX_THUMBNAIL/IMAGES/VENDOR/2026/6/15/6f892…` |
| `url` | string | `"https://www.swiggy.com/restaurants/pizza-h…` |
| `scraped_at` | string | `"2026-07-27T08:45:07.223Z"` |

#### Example output

```json
{
  "restaurant_id": "10575",
  "name": "Pizza Hut",
  "city": "bangalore",
  "area": "Central Bangalore",
  "locality": "Richmond Town",
  "cuisines": [
    "Pizzas"
  ],
  "rating": 4.3,
  "rating_count": "12K+",
  "cost_for_two": "₹600 for two",
  "delivery_time_mins": 27,
  "distance": "2.7 km",
  "offer": "ITEMS",
  "image_id": "RX_THUMBNAIL/IMAGES/VENDOR/2026/6/15/6f892224-627c-4702-89e5-430fb3637e58_10575.JPG",
  "url": "https://www.swiggy.com/restaurants/pizza-hut-10575",
  "scraped_at": "2026-07-27T08:45:07.223Z"
}
```

### Use cases

- **Restaurant market mapping** — see who operates in a city, in which cuisines, at what price point.
- **Competitive rating benchmarking** — compare a brand's rating and review volume against every competitor in the same locality.
- **Cloud-kitchen discovery** — brands appearing at many coordinates with identical menus are typically cloud kitchens.
- **Pricing analysis** — `cost_for_two` and the offer field together show real positioning versus list positioning.
- **Delivery-logistics research** — `delivery_time_mins` and `distance` across a coordinate grid reveal effective service radii.
- **Site selection** — cuisine density by locality highlights under-served pockets.

### FAQ

#### Why does the actor sample multiple coordinates?

Because Swiggy's listing surface is geo-indexed and caps at roughly 8-28 restaurants per coordinate. Requesting one point per city would silently return a fraction of the market and look like complete coverage. Sampling several points across the city and deduplicating is what makes city-level results real.

#### Can I target a specific neighbourhood?

Yes. Leave `latitude` and `longitude` blank to sample the whole city, or set them to pin the search to one point.

#### Is menu or dish-level data included?

No. This actor returns restaurant-level records. Menu extraction is a separate, much heavier job and is not claimed here.

#### Is `rating_count` a number?

It is Swiggy's own display string, such as '12K+', because that is the precision Swiggy publishes. Converting it would invent accuracy that the source does not have.

### Billing

Pay per event: one `restaurant-scraped` event per delivered record, charged only **after** the record is validated and stored. Empty results, blocked pages and duplicates are never charged. Store discounts apply automatically on paid Apify plans.

### Use in Claude, ChatGPT & any MCP agent

This actor runs as an MCP server, so an AI agent can call it directly:

```
https://mcp.apify.com/?tools=themineworks/swiggy-scraper
```

```python
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("themineworks/swiggy-scraper").call(run_input={"city": "bangalore", "maxResults": 10})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

### Legal and compliance

This actor collects only publicly available information — the same data any visitor can see without logging in. It does not access private or authenticated areas, does not attempt to bypass paywalls, and collects no personal data beyond what the source already publishes openly. You are responsible for using the output in line with the source site's terms and with the data protection law that applies to you.

MIT © [The Mine Works](https://apify.com/themineworks)

# Actor input Schema

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

Indian city to scrape.

## `latitude` (type: `string`):

Override the city centroid with an exact latitude.

## `longitude` (type: `string`):

Override the city centroid with an exact longitude.

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

Maximum restaurants to return.

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

Indian residential proxy is recommended.

## Actor input object example

```json
{
  "city": "bangalore",
  "maxResults": 10,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "IN"
  }
}
```

# 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": "bangalore",
    "maxResults": 10,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ],
        "apifyProxyCountry": "IN"
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("themineworks/swiggy-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": "bangalore",
    "maxResults": 10,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "IN",
    },
}

# Run the Actor and wait for it to finish
run = client.actor("themineworks/swiggy-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": "bangalore",
  "maxResults": 10,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "IN"
  }
}' |
apify call themineworks/swiggy-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/gdBEAGbd5h0kxDNc6/builds/yiyek5p6uavliXULv/openapi.json