McDonald's Store Details Scraper

Turn a list of McDonald's store page URLs into complete, structured store data — 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. Give it a list of McDonald's store page URLs and it returns one clean, structured record per store — 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: 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?

• 🔍 Extract full store details for any McDonald's US location — address, phone, latitude/longitude, and both dining-room and drive-thru hours
• 🕒 Live operational status — know whether a store is currently OPEN at scrape time
• 🧾 Amenities and features — drive-thru, WiFi, 24-hour service, mobile ordering, kiosk accessibility, gift cards, loyalty program, indoor dining, and more
• 🛵 Delivery-partner links — direct URLs to order from that store via DoorDash, Uber Eats, Grubhub, and McDonald's own delivery/order pages
• 💼 Careers/job URLs scoped to that specific location
• 🆔 Store and franchise identifiers — store number, internal store ID, region, co-op, and TV-market codes for franchise/market analysis
• ⚡ Fast, lightweight HTTP scraping — no headless browser required, so runs finish quickly and cheaply
• 📤 Export to JSON, CSV, Excel, HTML, or XML — download from the Output tab or pull via the Apify API
• 🔌 Full API access — run this Actor programmatically, schedule recurring runs, and connect it to Zapier, Make, or your own pipeline
• 📊 Built-in monitoring — 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 (or otherwise gather McDonald's store page URLs — 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 — or pull it programmatically via the Apify API.

Input

McDonald's Store Details Scraper takes just two inputs:

• Store URLs (links, required) — 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. Free-plan accounts process only the first 5 links per run — see Free vs. paid plan limits below.
• Max concurrency (maxConcurrency, optional, default 5) — how many store pages to fetch in parallel. Higher values finish faster but increase the chance of being rate-limited by McDonald's servers.

{
    "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 — 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 — 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 — there's nothing to configure. If you're on the free plan and need more than 5 stores per run, upgrade your Apify plan to remove the cap.

Output example

Every result is one structured JSON record per store:

{
    "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

• 📍 Store locator apps — power a "find your nearest McDonald's" feature with fresh address, hours, and amenity data
• 🥡 Food delivery and ordering platforms — pull direct DoorDash/Uber Eats/Grubhub links per store to route orders correctly
• 📈 Market and franchise research — analyze store density, amenities, and co-op/region distribution across markets
• 🕵️ Competitive intelligence — track which McDonald's locations offer 24-hour service, mobile ordering, or kiosk accessibility
• 🧭 Trip planning and logistics tools — check live open status and drive-thru hours before routing a visit
• 📊 Data enrichment pipelines — join scraped store IDs and coordinates with your own location datasets

McDonald's-related Actors

Actor	What it does
McDonald's Store Locator Scraper	Finds McDonald's store page URLs by city, state, or ZIP — 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 — 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 — you can start runs, poll status, and fetch results programmatically. See the Apify API documentation for details, or integrate it with Zapier / Make for no-code automation.

Can I schedule this Actor to run automatically?

Yes — 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 — custom development is available.