# McDonald's Store Details Scraper (`datacach/mcdonalds-store-details-scraper`) Actor
Scrape full McDonald's US restaurant details โ address, phone number, GPS coordinates, and opening hours โ for any store page URL. Feed it links from McDonald's Store Locator Scraper or your own list, and export structured JSON, CSV, or Excel data in seconds via the Apify API.
- **URL**: https://apify.com/datacach/mcdonalds-store-details-scraper.md
- **Developed by:** [DataCach](https://apify.com/datacach) (community)
- **Categories:** Developer tools, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.99 / 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.
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
## McDonald's Store Details Scraper
**Turn a list of McDonald's store page URLs into complete, structured store data** โ address, phone number, GPS coordinates, opening hours, live open/closed status, amenities, delivery links, and more. No coding required: paste your URLs, click **Start**, and **export** the results as JSON, CSV, or Excel in seconds via the Apify platform.
### What is McDonald's Store Details Scraper?
McDonald's Store Details Scraper is an **Apify Actor** that extracts full store-level **data** for any McDonald's restaurant in the US directly from the public **API** behind the [McDonald's store locator](https://www.mcdonalds.com/us/en-us/restaurant-locator.html). Give it a list of McDonald's store page URLs and it returns one clean, structured record per store โ no browser automation, no HTML parsing headaches, no manual copy-pasting from the website.
It's designed to slot right after the **[McDonald's Store Locator Scraper](https://apify.com/datacach/mcdonalds-store-locator-scraper)**: that Actor finds *which* stores exist and their page URLs; this Actor fills in *everything* about each one.
### What can McDonald's Store Details Scraper do?
- ๐ **Extract full store details** for any McDonald's US location โ address, phone, latitude/longitude, and both dining-room and drive-thru hours
- ๐ **Live operational status** โ know whether a store is currently `OPEN` at scrape time
- ๐งพ **Amenities and features** โ drive-thru, WiFi, 24-hour service, mobile ordering, kiosk accessibility, gift cards, loyalty program, indoor dining, and more
- ๐ต **Delivery-partner links** โ direct URLs to order from that store via DoorDash, Uber Eats, Grubhub, and McDonald's own delivery/order pages
- ๐ผ **Careers/job URLs** scoped to that specific location
- ๐ **Store and franchise identifiers** โ store number, internal store ID, region, co-op, and TV-market codes for franchise/market analysis
- โก **Fast, lightweight HTTP scraping** โ no headless browser required, so runs finish quickly and cheaply
- ๐ค **Export to JSON, CSV, Excel, HTML, or XML** โ download from the Output tab or pull via the Apify API
- ๐ **Full API access** โ run this Actor programmatically, schedule recurring runs, and connect it to **Zapier**, **Make**, or your own pipeline
- ๐ **Built-in monitoring** โ get run history, logs, and alerts on every execution from the Apify Console
### What data does McDonald's Store Details Scraper extract?
| Field | Description |
|---|---|
| `name` | Store brand name |
| `street`, `city`, `state`, `zipcode`, `country` | Store address |
| `full_address` | Pre-formatted `"City, ST ZIP"` address string |
| `short_description`, `long_description` | Landmark / cross-street label for the store (e.g. `"LINCOLN/TEXACO"`) |
| `phone` | Store phone number |
| `latitude`, `longitude` | GPS coordinates |
| `hours_raw` | Dining-room opening hours, per weekday |
| `drivethru_hours_raw` | Drive-thru opening hours, per weekday |
| `hours_today`, `drivethru_hours_today` | Today's dining-room and drive-thru hours |
| `timezone` | Store's local time zone |
| `open_status`, `status_code` | Live operational status (e.g. `OPEN`) and its numeric code |
| `amenities` | Amenities/features list (drive-thru, WiFi, 24-hour, mobile order, kiosk accessibility, gift cards, loyalty, indoor dining, and more) |
| `delivery_partners` | Delivery services available at this store, each with an `identifier`, `marketingName`, and `deliveryURL` (DoorDash, Uber Eats, Grubhub, etc.) |
| `restaurant_url`, `job_url` | Careers / job-listing URL for this specific location |
| `store_number` | McDonald's store number (`NatlStrNumber`) |
| `store_id` | Composite internal store ID |
| `store_identifiers` | Internal franchise/market identifiers (Entity, Region ID, Co-Op, TV-Market, etc.) |
| `extraction_datetime`, `extraction_date` | UTC timestamp and date the record was scraped |
### How do I use McDonald's Store Details Scraper to get McDonald's store details?
1. Run the **[McDonald's Store Locator Scraper](https://apify.com/datacach/mcdonalds-store-locator-scraper)** (or otherwise gather McDonald's store page URLs โ one per restaurant).
2. Open this Actor's **Input** tab and paste those URLs into **Store URLs**.
3. Optionally adjust **Max concurrency** to control how many stores are fetched in parallel (default: 5).
4. Click **Start**.
5. When the run finishes, open the **Output** tab and export your data as JSON, CSV, Excel, HTML, or XML โ or pull it programmatically via the [Apify API](https://docs.apify.com/api/v2).
### Input
McDonald's Store Details Scraper takes just two inputs:
- **Store URLs** (`links`, required) โ a list of McDonald's store page URLs, e.g. `https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html`. Typically produced by [McDonald's Store Locator Scraper](https://apify.com/datacach/mcdonalds-store-locator-scraper). Free-plan accounts process only the first 5 links per run โ see [Free vs. paid plan limits](#free-vs-paid-plan-limits) below.
- **Max concurrency** (`maxConcurrency`, optional, default `5`) โ how many store pages to fetch in parallel. Higher values finish faster but increase the chance of being rate-limited by McDonald's servers.
```json
{
"links": ["https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html"],
"maxConcurrency": 5
}
````
### Free vs. paid plan limits
McDonald's Store Details Scraper behaves differently depending on your Apify account plan:
| | Free plan | Paid plan |
|---|---|---|
| **Store URLs processed per run** | First 5 unique links only โ any extra links in your input are ignored | All links you provide, no cap |
| **Max concurrency** | Up to 20 (same as paid) | Up to 20 |
| **Output fields** | Full data for every processed store โ no fields withheld | Full data for every processed store |
| **Best for** | Trying the Actor out, small one-off lookups | Bulk lookups, franchise-wide or nationwide store data, production pipelines |
Your plan is detected automatically at run time โ there's nothing to configure. If you're on the free plan and need more than 5 stores per run, [upgrade your Apify plan](https://apify.com/pricing) to remove the cap.
### Output example
Every result is one structured JSON record per store:
```json
{
"url": "https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html",
"name": "McDonald's",
"street": "972 8th Ave",
"city": "New York",
"state": "NY",
"zipcode": "10019",
"country": "United States",
"full_address": "New York, NY 10019",
"short_description": "8TH AVE",
"long_description": "972 8TH AVENUE",
"phone": "(212) 582-1032",
"latitude": 40.764708,
"longitude": -73.983773,
"hours_raw": { "hoursMonday": "05:00 - 23:00" },
"drivethru_hours_raw": { "driveHoursMonday": "05:00 - 23:00" },
"hours_today": "05:00 - 23:00",
"drivethru_hours_today": "05:00 - 23:00",
"timezone": "(GMT-05:00) Eastern Time (US & Canada)",
"open_status": "OPEN",
"status_code": 1,
"amenities": ["DRIVETHRU", "WIFI", "MOBILEORDERS", "GIFTCARDS", "LOYALTY", "INDOORDINING"],
"delivery_partners": [
{ "identifier": "UBEREATS", "marketingName": "Uber Eats", "deliveryURL": "https://www.ubereats.com/store/..." }
],
"restaurant_url": "https://jobs.mchire.com/jobs?s=972+8th+Ave%2c+New+York%2c+NY",
"job_url": "https://jobs.mchire.com/jobs?s=972+8th+Ave%2c+New+York%2c+NY",
"store_number": "3906",
"store_id": "195500293691:en-US",
"store_identifiers": { "NATLSTRNUMBER": "3906", "Entity": "22602", "Region ID": "28" },
"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** directly from the Output tab, or retrieve it programmatically through the Apify API.
### Use cases
- ๐ **Store locator apps** โ power a "find your nearest McDonald's" feature with fresh address, hours, and amenity data
- ๐ฅก **Food delivery and ordering platforms** โ pull direct DoorDash/Uber Eats/Grubhub links per store to route orders correctly
- ๐ **Market and franchise research** โ analyze store density, amenities, and co-op/region distribution across markets
- ๐ต๏ธ **Competitive intelligence** โ track which McDonald's locations offer 24-hour service, mobile ordering, or kiosk accessibility
- ๐งญ **Trip planning and logistics tools** โ check live open status and drive-thru hours before routing a visit
- ๐ **Data enrichment pipelines** โ join scraped store IDs and coordinates with your own location datasets
### McDonald's-related Actors
| Actor | What it does |
|---|---|
| [McDonald's Store Locator Scraper](https://apify.com/datacach/mcdonalds-store-locator-scraper) | Finds McDonald's store page URLs by city, state, or ZIP โ feed the output straight into this Actor |
### FAQ
#### Is it legal to scrape McDonald's store data?
This Actor only collects **publicly available data** from the same anonymous API that powers the official McDonald's store locator website โ the same information any visitor can already see. That said, scraping public data may still be subject to a target site's Terms of Service, so review McDonald's terms and your local regulations before using this data commercially, and avoid collecting personal or sensitive information.
#### Does McDonald's Store Details Scraper have an API?
Yes. Every Apify Actor, including this one, is automatically exposed as an **API endpoint** โ you can start runs, poll status, and fetch results programmatically. See the [Apify API documentation](https://docs.apify.com/api/v2) for details, or integrate it with **Zapier** / **Make** for no-code automation.
#### Can I schedule this Actor to run automatically?
Yes โ use the **Schedule** feature in the Apify Console to run this Actor on a recurring basis (e.g. nightly) to keep your store data fresh, and get notified on failures via built-in monitoring.
#### Why did some links fail or come back empty?
A link may fail if the store page URL is invalid, the store ID can't be resolved, or McDonald's anti-bot protection temporarily blocks the request. Failed and blocked links are logged and skipped; the run only fails if **no** link succeeds. Re-running usually resolves transient blocks.
#### What's the difference between `hours_raw` and `hours_today`?
`hours_raw` is the full weekly schedule (one entry per day). `hours_today` is a convenience field with just the current day's hours, so you don't have to parse the weekly object if you only need "is it open right now."
### Support
Found a bug or have a feature request? Open an issue on this Actor's **Issues** tab in Apify Console. Need a custom scraping solution or McDonald's data pipeline built for your use case? Reach out through the Actor's contact page โ custom development is available.
# Actor input Schema
## `links` (type: `array`):
McDonald's store page URLs to extract details from, e.g. https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html. Typically the output of McDonald's Store Locator Scraper. Duplicate URLs are automatically removed. Free plan accounts process only the first 5 links.
## `maxConcurrency` (type: `integer`):
How many store pages to fetch in parallel. Higher values finish faster but increase the chance of being rate-limited by McDonald's servers โ 5 is a safe default.
## Actor input object example
```json
{
"links": [
"https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html"
],
"maxConcurrency": 5
}
```
# 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 = {
"links": [
"https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("datacach/mcdonalds-store-details-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ 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);
});
// ๐ Want to learn more ๐? Go to โ 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 = { "links": ["https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html"] }
# Run the Actor and wait for it to finish
run = client.actor("datacach/mcdonalds-store-details-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"links": [
"https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html"
]
}' |
apify call datacach/mcdonalds-store-details-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=datacach/mcdonalds-store-details-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "McDonald's Store Details Scraper",
"description": "Scrape full McDonald's US restaurant details โ address, phone number, GPS coordinates, and opening hours โ for any store page URL. Feed it links from McDonald's Store Locator Scraper or your own list, and export structured JSON, CSV, or Excel data in seconds via the Apify API.",
"version": "0.0",
"x-build-id": "zNGdQQInbDN43RzNk"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/datacach~mcdonalds-store-details-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-datacach-mcdonalds-store-details-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/datacach~mcdonalds-store-details-scraper/runs": {
"post": {
"operationId": "runs-sync-datacach-mcdonalds-store-details-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/datacach~mcdonalds-store-details-scraper/run-sync": {
"post": {
"operationId": "run-sync-datacach-mcdonalds-store-details-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": [
"links"
],
"properties": {
"links": {
"title": "Store URLs",
"type": "array",
"description": "McDonald's store page URLs to extract details from, e.g. https://www.mcdonalds.com/us/en-us/location/ny/new-york/972-8th-ave/3906.html. Typically the output of McDonald's Store Locator Scraper. Duplicate URLs are automatically removed. Free plan accounts process only the first 5 links.",
"items": {
"type": "string"
}
},
"maxConcurrency": {
"title": "Max concurrency",
"minimum": 1,
"maximum": 20,
"type": "integer",
"description": "How many store pages to fetch in parallel. Higher values finish faster but increase the chance of being rate-limited by McDonald's servers โ 5 is a safe default.",
"default": 5
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```