# Rappi Scraper (`scrapers_lat/rappi-scraper`) Actor
Scrape restaurants and stores from Rappi Colombia! Extract store name, logo, category, rating, delivery time and fee, address, city and store ID, plus full menus with product name, price, description and image, and opening hours.
- **URL**: https://apify.com/scrapers\_lat/rappi-scraper.md
- **Developed by:** [Michael Flores](https://apify.com/scrapers_lat) (community)
- **Categories:** E-commerce, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $8.00 / 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## Rappi Scraper
> Extract restaurant and store listings with full menus from Rappi, the leading food and grocery delivery platform in Colombia with thousands of partner stores across Bogotá, Medellín, Cali and Barranquilla.
22 fields per record
4 cities Colombia coverage
JSON / CSV / Excel output formats
Updated 2026-06-19
### What you get
Each record is one restaurant or store, ready to load into a database, spreadsheet, or analytics pipeline:
- **imageUrl**: store logo image
- **name**: store name as listed
- **url**: direct link to the store page on Rappi
- **storeId**: unique Rappi store identifier
- **brandName**: parent brand of the store
- **storeType**: store type (restaurant)
- **category**: cuisine categories such as Pizza, Hamburguesa, Sushi, Pollo
- **rating**: average customer rating
- **reviewCount**: number of customer reviews
- **deliveryTime**: estimated delivery time
- **deliveryFee**: delivery price in local currency
- **deliveryMethods**: available methods such as delivery and pickup
- **address**: street address of the store
- **city**: city of the store
- **country**: country of the store
- **status**: whether the store is open or closed
- **isExclusive**: whether the store is exclusive to Rappi
- **backgroundImage**: store cover image
- **menu\***: full product list with name, category, price, real price, description and image
- **productCount\***: number of menu products found
- **hours\***: weekly opening hours per day
- **detailAddress\***: address from the store detail page
- **observedAt**: when this store was last seen by the scraper
*\*These fields only appear when withDetails is set to true.*
### Who is it for
| Use case | Who benefits |
|---|---|
| Menu and price monitoring | Restaurants tracking competitor menus and delivery fees |
| Market research | Analysts studying food delivery supply and pricing |
| Lead generation | Sales teams building lists of restaurants on Rappi |
| Data pipelines | Developers feeding BI tools or recommendation engines |
| Academic research | Researchers studying the LATAM delivery economy |
### Frequently Asked Questions
**Which cities and country does this Rappi scraper cover?**
It covers Rappi Colombia across Bogotá, Medellín, Cali and Barranquilla. Each city exposes between roughly 3,000 and 5,400 restaurants, and you select the city in the input.
**How many restaurants can I collect per run?**
You can collect from a handful up to several thousand stores per city, controlled by the Max Items input. The scraper pages through the full store list of the selected city in batches.
**Can I filter restaurants by cuisine or category?**
Yes. Set the Category input to a cuisine name such as Pizza, Hamburguesa, Sushi, Pollo or Desayunos, and only stores tagged with that category are returned.
**How do I get the full menu of each restaurant?**
Enable the With Details option. For each store the scraper then fetches its complete menu, with product names, prices, descriptions and images, plus opening hours and the store address.
**What happens when a store has no rating or is closed?**
Those fields reflect the live store state. A store with no reviews returns a null rating and a zero review count, and the status field shows whether it is currently open or closed.
---
> This actor is an independent tool and has no affiliation with Rappi. It only accesses data that is publicly available on the platform. Use it in accordance with Rappi's terms of service.
# Actor input Schema
## `startUrl` (type: `string`):
Optional. A single Rappi restaurant/store page URL (e.g. https://www.rappi.com.co/restaurantes/delivery/121-empanaditas). When set, only that store is scraped. Leave empty to scrape a city listing.
## `country` (type: `string`):
Rappi country to scrape. Determines the domain, language and proxy country.
## `city` (type: `string`):
City to scrape within Colombia.
## `category` (type: `string`):
Optional. Filter stores by cuisine category name, e.g. Hamburguesa, Pizza, Sushi, Pollo, Saludable, Desayunos. Matched against each store's category tags.
## `maxItems` (type: `integer`):
Maximum number of stores to collect. Optional.
## `withDetails` (type: `boolean`):
When enabled, each store is enriched with its full menu (products with name, price, description, image) and opening hours. Slower.
## Actor input object example
```json
{
"country": "CO",
"city": "Bogotá",
"maxItems": 10,
"withDetails": false
}
````
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"startUrl": "",
"category": "",
"maxItems": 10
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/rappi-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"startUrl": "",
"category": "",
"maxItems": 10,
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/rappi-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 '{
"startUrl": "",
"category": "",
"maxItems": 10
}' |
apify call scrapers_lat/rappi-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/rappi-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Rappi Scraper",
"description": "Scrape restaurants and stores from Rappi Colombia! Extract store name, logo, category, rating, delivery time and fee, address, city and store ID, plus full menus with product name, price, description and image, and opening hours.",
"version": "0.1",
"x-build-id": "UxsNAN0bRjMSETL0T"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~rappi-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-rappi-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~rappi-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-rappi-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~rappi-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-rappi-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"country"
],
"properties": {
"startUrl": {
"title": "Store URL",
"type": "string",
"description": "Optional. A single Rappi restaurant/store page URL (e.g. https://www.rappi.com.co/restaurantes/delivery/121-empanaditas). When set, only that store is scraped. Leave empty to scrape a city listing."
},
"country": {
"title": "Country",
"enum": [
"CO"
],
"type": "string",
"description": "Rappi country to scrape. Determines the domain, language and proxy country.",
"default": "CO"
},
"city": {
"title": "City",
"enum": [
"Bogotá",
"Medellín",
"Cali",
"Barranquilla"
],
"type": "string",
"description": "City to scrape within Colombia.",
"default": "Bogotá"
},
"category": {
"title": "Category",
"type": "string",
"description": "Optional. Filter stores by cuisine category name, e.g. Hamburguesa, Pizza, Sushi, Pollo, Saludable, Desayunos. Matched against each store's category tags."
},
"maxItems": {
"title": "Max Items",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of stores to collect. Optional."
},
"withDetails": {
"title": "With Details (menu, hours)",
"type": "boolean",
"description": "When enabled, each store is enriched with its full menu (products with name, price, description, image) and opening hours. Slower.",
"default": false
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```