Mexico

Mexico Food Data API: Rappi, DiDi Food and Uber Eats Menu Data

FoodSpark’s Mexico food data API delivers restaurant, menu, and delivery data from Rappi, DiDi Food, and Uber Eats. You can then get it as JSON, CSV, or a live API feed. Every record also carries the state, city, colonia, and postal code. So you can compare Mexico City, Guadalajara, and Monterrey fairly.

In short, you get:

• Delivery app data: restaurants, menus, prices, fees, promos and ratings
• Menu details: dishes, combos, sizes, add-ons and Spanish item names
• Mexico-ready fields: peso prices, IVA flags, colonias and five-digit postal codes
• Flexible delivery: a one-off dataset, a scheduled feed or live API access

Why the Mexico Food Data API Needs Local Detail

Mexico’s delivery market, however, has its own tax rules, price laws, and a close three-way race. So, data that ignores them leads to unfair comparisons. That is why our Mexico food data API captures each local detail as its own field.

• A big market: Mexico is Latin America’s second-largest delivery market after Brazil. In 2024, it was worth about US$2.5 billion, according to Statista.
• A close race: DiDi Food had 38% of delivery-app monthly users in 2024 (to August), per Sensor Tower. Rappi had 36%. Meanwhile, Uber Eats expanded to 10 more southeastern cities in 2024.
• One tax rate for delivery: Prepared food carries 16% IVA, including takeaway and home delivery. So, we flag the rate on every item.
• Tax-inclusive prices: By law, sellers must show the total price, including taxes and fees. Therefore, we record both the menu price and the full checkout cost, where shown.
• New rider rules: A labour law reform for platform workers took effect in mid-2025. Then, during a pilot from July to December 2025, about 912,000 app workers gained social security. So, we track delivery fees over time to show any change.

Mexico Food Data API at a Glance

Sources Covered by the Mexico Food Data API

The Mexico Food Data API collects public data from the apps and chains Mexican diners use most. Then we merge it into one clean dataset. Each linked name also opens its full API page.

Delivery Apps

So why not use the apps’ own APIs? Rappi and Uber Eats do offer APIs, but only to their partner restaurants. DiDi Food, meanwhile, connects through integration partners. However, these tools only show your own stores and orders. By contrast, the Mexico food data API shows the whole market in the postal codes you choose.

Restaurant Chains

Chains: we also cover chains such as Starbucks, Domino’s, and McDonald’s. For example, Alsea ran 951 Starbucks and 992 Domino’s stores in Mexico in mid-2026. In addition, digital sales, including delivery apps, made up 40.7% of Alsea’s sales across all its markets.

Need a source that is not listed? Then we build a custom crawler and add it to your Mexico food data API feed.

Data Fields in the Mexico Food Data API

Every Mexico food data API record uses the same clean field names. As a result, you can join Rappi, DiDi Food, and Uber Eats data without extra work.

Restaurant and Menu Fields

Fee and Offer Fields

Mexico-Only Extras

• IVA flag: the 16% rate on prepared food, per item
• Total price: the checkout total with taxes and fees, where shown
• Colonia: the neighbourhood name used in Mexican addresses
• Local text: dish names stay in Spanish, while an English category is optional

Cities and States in the Mexico Food Data API

The Mexico food data API covers every area a source app serves. Even so, the big cities matter most, since all three apps compete there. DiDi Food alone had delivered in more than 60 Mexican cities by 2025, Expansión reported.

For example, you can compare one taco chain’s prices in Mexico City and Monterrey. Likewise, you can check how delivery fees change from one colonia to the next.

How the Mexico Food Data API Maps Postal Codes

Mexican postal codes have five digits, such as 06600 in Mexico City. Then the Mexico Food Data API adds the state, city, colonia, and coordinates to each record. As a result, you can roll data up from one street to all 32 federal entities.

Sample Record From the Mexico Food Data API

Below, for example, is a shortened record from the Mexico Food Data API. The restaurant and values are examples only.

{
  "platform": "rappi_mx",
  "restaurant_id": "rp_mx_730115",
  "restaurant_name": "Taquería Ejemplo",
  "state": "Ciudad de México",
  "city": "Cuauhtémoc",
  "colonia": "Juárez",
  "postal_code": "06600",
  "item_name": "Orden de tacos al pastor (5 pzas)",
  "item_name_en": "Al pastor tacos, order of 5",
  "item_price_mxn": 115.00,
  "iva_rate": 0.16,
  "tax_included": true,
  "delivery_fee_mxn": 29.00,
  "service_fee_mxn": 9.00,
  "promo": "Envío gratis en pedidos de $199+",
  "rating": 4.7,
  "delivery_time_min": "25-35",
  "collected_at": "2026-10-07T13:00:00-06:00"
}

Formats and Delivery

You can get the data as JSON, CSV, Excel, or XML. In addition, we can push it to a database, cloud storage, or your own endpoint. Refresh rates, meanwhile, range from real-time and daily to weekly or monthly.

How It Works

1. Share your needs: tell us the apps, cities, and fields you want.
2. Review a sample: check a free Mexico sample first.
3. Set up the feed: then we configure crawlers, schedules, and quality checks.
4. Stay covered: finally, we fix the crawlers whenever an app changes.

What Teams Do With the Mexico Food Data API

Teams use the Mexico food data API to follow a three-app market where promos change often. For example, they:

1. Compare platforms: check the same restaurant’s price on Rappi, DiDi Food, and Uber Eats.
2. Track promos: see which apps and restaurants run discounts and free delivery.
3. Watch fees: follow delivery and service fees as rider rules settle in.
4. Benchmark chains: compare Starbucks, Domino’s and local taco chains by state.
5. Plan expansion: compare restaurant counts and fees by city before you launch.
6. Feed AI and dashboards: use fresh, structured data instead of reports that go stale.

Because prices, fees, and promos keep shifting, a one-off report ages fast. So a scheduled feed usually works better.

Mexico Food Data API: FAQs

What is a Mexico food data API?

A Mexico food data API gives your software structured data from Mexican delivery apps and restaurants. For example, it includes menus, prices, fees, promos, and ratings. So your apps and dashboards always work with fresh data.

Can you extract Rappi and DiDi Food data in Mexico?

Yes. We collect public Rappi, DiDi Food, and Uber Eats menus, prices, fees, promos, and ratings by city or postal code. In addition, each dish stays linked to its restaurant ID.

How do you handle IVA?

Prepared food in Mexico carries 16% IVA, even for delivery. So we tag each item with that rate. We also record whether the shown price already includes it.

Do app prices match in-store prices?

Not always, since restaurants can set different prices on each app. That is why we collect prices from every app separately. You can then compare them side by side.

Is the data legally sourced?

We collect only public listing data, such as menus, prices, ratings, and availability. In other words, we never collect personal or login-protected data. We also design the feed with Mexico’s 2025 personal data protection law in mind.

How do I get a free sample?

Just tell us the app, city, and fields you need. Then we send a free sample, usually as JSON or CSV.