# Chipotle Locations Scraper (`datacach/chipotle-locations-scraper`) Actor
Scrape all Chipotle restaurant location URLs across the US from the public store locator sitemap. Export links for every store, no coordinates needed. Try it free.
- **URL**: https://apify.com/datacach/chipotle-locations-scraper.md
- **Developed by:** [DataCach](https://apify.com/datacach) (community)
- **Categories:** Automation, Developer tools, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.49 / 1,000 links
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/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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
## Chipotle Locations Scraper
**Extract every Chipotle restaurant page URL** in the US directly from Chipotle's public [store locator sitemap](https://locations.chipotle.com/sitemap.xml) — no browser, no login, no API key. This **Chipotle scraper** walks the sitemap index, filters out non-store pages, and returns one clean, deduplicated link per restaurant, ready to feed into further scraping, geocoding, or a metadata Actor.
Run it on demand or on a **schedule**, pull results through the **Apify API**, and connect it to **Zapier, Make, or n8n** for hands-off delivery of fresh Chipotle location data.
### What can Chipotle Locations Scraper do?
- 🌮 **Scrapes the full Chipotle store locator sitemap** — every US restaurant page URL, filtered to real store pages (ordering pages excluded).
- 🔗 **Deduplicates automatically** — each restaurant URL appears once, even if the sitemap changes between requests.
- 🎯 **Max results control** — collect a quick sample (default 50) or set `0` to pull the entire catalog (~4,000+ links).
- ⏭️ **Resumable pagination** — `startIndex` and `excludeUrls` let you pick up where a previous run left off without re-collecting (or re-paying for) links you already have.
- 🔁 **Crash-safe checkpointing** — a migrated or restarted run resumes from where it stopped instead of starting over.
- 📤 **Multiple export formats** — download results as **JSON, CSV, Excel, or HTML** straight from the Output tab.
- ☁️ **Built for the Apify platform** — schedule recurring runs, trigger via the **REST API**, monitor run history, and integrate with Zapier/Make/n8n webhooks.
- 🤝 **Pairs with the Chipotle Restaurant Metadata Actor** to turn these links into full store details (address, phone, geolocation, hours).
### What data does Chipotle Locations Scraper extract?
Each dataset item represents one Chipotle restaurant page link:
| Field | Description |
|---|---|
| `url` | Full URL of the Chipotle restaurant location page |
| `coordinate` | Source label identifying where the link was discovered (currently `static source`) |
| `extraction_datetime` | UTC timestamp (ISO 8601) when the link was collected |
| `extraction_date` | Extraction date in `mm-dd-yyyy` format |
### How do I use Chipotle Locations Scraper to scrape Chipotle store URLs?
1. Click **Try for free** or open the Actor and go to the **Input** tab.
2. Optionally set **Max results**, **Start index**, and/or **Exclude collected links** — see [Input](#input) below. The defaults work out of the box.
3. Click **Start** and wait for the run to finish.
4. Open the **Output** tab and export your Chipotle location links as **JSON, CSV, Excel, or HTML**.
### Input
The Actor accepts three optional inputs — you can also just click **Start** and use the defaults:
- **Max results** — the maximum number of unique restaurant links to collect in this run. Default is `50`. Set it to `0` to collect every Chipotle location in the sitemap (roughly 4,000+ links); since this Actor can be billed per result, raise it gradually rather than jumping straight to `0`.
- **Start index** — skips this many links from the start before saving any, letting you paginate across multiple runs (e.g. set `500` to continue after already collecting the first 500) without paying again for links you already have.
- **Exclude collected links** — a list of restaurant URLs you already have. Any link on this list is never saved again, regardless of order — useful when you keep a running list and only want new locations.
Free-plan runs are capped at 10 links per run, and **Start index** / **Exclude collected links** are disabled on the free plan to prevent bypassing that cap.
### Output example
```json
{
"url": "https://locations.chipotle.com/al/birmingham/300-20th-st-s",
"coordinate": "static source",
"extraction_datetime": "2026-07-21T14:30:00.123456+00:00",
"extraction_date": "07-21-2026"
}
````
You can download the dataset in various formats such as **JSON, HTML, CSV, or Excel**.
### Use cases
- **Build a Chipotle store directory** for a food-delivery, aggregator, or comparison app.
- **Feed restaurant URLs into a metadata scraper** (like the Chipotle Restaurant Metadata Actor) to pull addresses, phone numbers, hours, and geolocation for every store.
- **Track new Chipotle store openings** by scheduling recurring runs and comparing link counts over time.
- **Power location-based search or store-locator features** in an internal tool without hand-maintaining a URL list.
- **Feed a market-research or site-expansion dataset** with the full list of active Chipotle locations across the US.
### Chipotle-related Actors
| Actor | What it does |
|---|---|
| Chipotle Restaurant Metadata *(placeholder)* | Takes links from this Actor and extracts address, phone, geolocation, and hours for each store |
### FAQ
#### Is it legal to scrape Chipotle locations?
This Actor only collects **publicly available data** from Chipotle's public sitemap — the same URLs search engines index. It does not bypass logins, paywalls, or access any private data. That said, scraping is subject to the target site's Terms of Service; review Chipotle's terms and applicable law before using the extracted data commercially, and consult a legal professional if you're unsure.
#### Does this Actor extract store hours, phone numbers, or coordinates?
No — this Actor only collects restaurant **page URLs**. Pair it with the Chipotle Restaurant Metadata Actor to pull hours, phone numbers, addresses, and geolocation for each link.
#### What's the difference between the free and paid plan?
Free-plan runs are capped at **10 links**, and both **Start index** and **Exclude collected links** are disabled (forced to their defaults) so a free run can't bypass the cap by paginating across multiple runs.
#### Can I resume a run without paying twice for the same links?
Yes. If a run is interrupted (e.g. platform migration), it resumes from its checkpoint instead of starting over, so already-collected links aren't re-pushed. Across separate runs, use **Start index** and **Exclude collected links** to avoid re-collecting links you already have.
#### Is there an API for this Actor?
Yes — every Apify Actor run can be triggered and its results retrieved via the [Apify API](https://docs.apify.com/api/v2), so you can integrate this scraper into your own app, script, or automation (Zapier, Make, n8n) without touching the Apify Console.
#### What if the sitemap request gets blocked?
If Chipotle's sitemap blocks the request (anti-bot protection), the affected request is logged and the run fails gracefully rather than returning partial or corrupted data.
### Support
Found a bug or have a feature request? Open an issue on the Actor's **Issues** tab in Apify Console. Need a custom version of this scraper — different data fields, another region, or a fully managed pipeline? Reach out through the Actor's contact page for a custom solution.
# Actor input Schema
## `maxResults` (type: `integer`):
Maximum number of unique restaurant links to collect this run. Set 0 to collect every restaurant in the sitemap (roughly 4,000+ links) — this can take a while and, under pay-per-result pricing, may cost more than expected, so raise it gradually. Free plan is capped at 10 links regardless of this setting.
## `startIndex` (type: `integer`):
Skip this many links from the start before saving any. Use it to paginate across runs: if you already have the first 500, set 500 to begin from link 501 and avoid paying again for links you already have. Links are discovered in a stable order from the sitemap, so index N is reproducible between runs as long as Chipotle's sitemap ordering doesn't change. The Actor still crawls up to that point, so a large value does not make the run faster — it only changes which links are saved. Combined with Max results, the saved range is \[startIndex, startIndex + maxResults). Ignored on the free plan (always starts from 0).
## `excludeUrls` (type: `array`):
Restaurant links you already have, e.g. https://locations.chipotle.com/al/birmingham/300-20th-st-s. Any URL listed here is never saved again, regardless of order. Unlike Start index, this is order-independent — ideal when you keep a running list and only want new links. Applied after Start index. Free plan runs may list at most 1 URL here.
## Actor input object example
```json
{
"maxResults": 50,
"startIndex": 0,
"excludeUrls": [
"https://locations.chipotle.com/al/birmingham/300-20th-st-s"
]
}
```
# Actor output Schema
## `dataset` (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 = {
"maxResults": 50,
"excludeUrls": [
"https://locations.chipotle.com/al/birmingham/300-20th-st-s"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("datacach/chipotle-locations-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 = {
"maxResults": 50,
"excludeUrls": ["https://locations.chipotle.com/al/birmingham/300-20th-st-s"],
}
# Run the Actor and wait for it to finish
run = client.actor("datacach/chipotle-locations-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 '{
"maxResults": 50,
"excludeUrls": [
"https://locations.chipotle.com/al/birmingham/300-20th-st-s"
]
}' |
apify call datacach/chipotle-locations-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=datacach/chipotle-locations-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Chipotle Locations Scraper",
"description": "Scrape all Chipotle restaurant location URLs across the US from the public store locator sitemap. Export links for every store, no coordinates needed. Try it free.",
"version": "0.0",
"x-build-id": "0gcygQUVwfvNrHHkV"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/datacach~chipotle-locations-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-datacach-chipotle-locations-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/datacach~chipotle-locations-scraper/runs": {
"post": {
"operationId": "runs-sync-datacach-chipotle-locations-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/datacach~chipotle-locations-scraper/run-sync": {
"post": {
"operationId": "run-sync-datacach-chipotle-locations-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",
"properties": {
"maxResults": {
"title": "Max results",
"minimum": 0,
"type": "integer",
"description": "Maximum number of unique restaurant links to collect this run. Set 0 to collect every restaurant in the sitemap (roughly 4,000+ links) — this can take a while and, under pay-per-result pricing, may cost more than expected, so raise it gradually. Free plan is capped at 10 links regardless of this setting.",
"default": 50
},
"startIndex": {
"title": "Start index",
"minimum": 0,
"type": "integer",
"description": "Skip this many links from the start before saving any. Use it to paginate across runs: if you already have the first 500, set 500 to begin from link 501 and avoid paying again for links you already have. Links are discovered in a stable order from the sitemap, so index N is reproducible between runs as long as Chipotle's sitemap ordering doesn't change. The Actor still crawls up to that point, so a large value does not make the run faster — it only changes which links are saved. Combined with Max results, the saved range is [startIndex, startIndex + maxResults). Ignored on the free plan (always starts from 0).",
"default": 0
},
"excludeUrls": {
"title": "Exclude collected links",
"type": "array",
"description": "Restaurant links you already have, e.g. https://locations.chipotle.com/al/birmingham/300-20th-st-s. Any URL listed here is never saved again, regardless of order. Unlike Start index, this is order-independent — ideal when you keep a running list and only want new links. Applied after Start index. Free plan runs may list at most 1 URL here.",
"default": [],
"items": {
"type": "string"
}
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```