# Wendy's Menu Scraper: Store Prices & Calories (`memo23/wendys-menu-scraper`) Actor

Wendy's menu data at store level. Give it a street address, ZIP or restaurant number and get ~150 products with the location's real prices, calories, categories and combo flags. Optional descriptions and customisations. Batch any number of stores. Pure HTTP. JSON or CSV.

- **URL**: https://apify.com/memo23/wendys-menu-scraper.md
- **Developed by:** [Muhamed Didovic](https://apify.com/memo23) (community)
- **Categories:** E-commerce, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.70 / 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.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Wendy's Menu Scraper

<p align="center"><img src="https://raw.githubusercontent.com/muhamed-didovic/muhamed-didovic.github.io/main/assets/wendys/logo.png" width="140" alt="Wendy's Menu Scraper"></p>

**Paste a street address, get that Wendy's actual menu.** Prices as that restaurant charges them, calories on every item, all 15 menu categories, combos and Limited Time Offers flagged, and — optionally — full item descriptions and customisation options. Batch as many locations as you like in one run.

| Input | Rows emitted |
|---|---|
| `345 Valley Avenue, Birmingham, AL 35209` | ~150 products at the restaurant nearest that address |
| `35209` (ZIP) | ~150 products at the nearest restaurant in that ZIP |
| `Birmingham, AL` (city) | ~150 products at the nearest restaurant in that city |
| Restaurant number `1252` | ~150 products at that exact store, menu only |

> Pure HTTP. No browser, no proxy, no API key, no login.

### How it works

<p align="center"><img src="https://raw.githubusercontent.com/muhamed-didovic/muhamed-didovic.github.io/main/assets/wendys/how-it-works.png" alt="How the Wendy's Menu Scraper works"></p>

Every location you supply goes straight to Wendy's own location search, which geocodes it and returns the nearest restaurants with their full address, hours and phone. Because Wendy's does the geocoding, spelling and abbreviations never matter — "Road" or "Rd", "West" or "W" resolve to the same store. The menu is then read for that specific restaurant, so the prices are the ones that location charges.

Those prices are genuinely per-store. A Baconator® is $7.99 in Birmingham and $9.99 in Times Square; across those two restaurants, 88 of the shared items priced differently. A national menu would hide every one of those gaps.

### Input

| Field | Type | Required | Notes |
|---|---|---|---|
| `addresses` | array of strings | one of these two | Street addresses, ZIP codes or city names. Mix them freely. |
| `restaurantIds` | array of strings | one of these two | Wendy's restaurant numbers, e.g. `1252`. Skips the location search. |
| `maxStoresPerAddress` | integer | no | Restaurants per location, nearest first. Default `1`. |
| `searchRadiusMiles` | integer | no | How far to look around each location. Default `25`. |
| `categories` | array of strings | no | Limit to these category names (case-insensitive). Empty = whole menu. |
| `includeDetails` | boolean | no | Add each item's description and customisation options. Default `false`. |
| `maxItems` | integer | no | Row cap. Default `5000` (about 33 restaurants). |
| `maxConcurrency` | integer | no | Parallel HTTP calls. Default `8`. |
| `proxy` | object | no | Optional. The actor runs direct by default. |

#### Example input

```json
{
  "addresses": ["345 Valley Avenue, Birmingham, AL 35209", "Times Square, New York, NY 10036"],
  "maxStoresPerAddress": 1,
  "includeDetails": false,
  "maxItems": 5000
}
```

### Output schema

One row per product per restaurant. A product listed in more than one category is emitted once, under the first category it appears in.

```jsonc
{
  "type": "menu-item",

  "restaurantId": "1252",
  "storeName": "VALLEY AVE-252",
  "storeAddress": "345 VALLEY AVE",
  "storeCity": "BIRMINGHAM",
  "storeState": "AL",
  "storePostalCode": "35209",
  "storeCountry": "US",
  "storeLatitude": 33.4715,
  "storeLongitude": -86.823,
  "storePhone": "2059427007",
  "searchedAddress": "345 Valley Avenue, Birmingham, AL 35209",  // echoes your input

  "itemId": "30003",
  "itemName": "Baconator®",
  "slug": "baconator",
  "categoryId": "100",
  "categoryName": "Hamburgers",

  "price": 7.99,                 // this restaurant's price, in USD
  "currency": "USD",
  "calories": 890,

  "isCombo": false,
  "isLimitedTimeOffer": false,
  "isFreestyle": false,
  "hasRequiredModifiers": false,
  "imageId": "2388",

  // present only when includeDetails is on:
  "description": "A half-pound* of fresh, never-frozen beef, American cheese, 6 pieces of crispy Applewood smoked bacon…",
  "modifiers": [
    { "name": "Applewood Smoked Bacon", "description": "…" },
    { "name": "Cheese", "description": "…" }
  ],
  "allergens": null,

  "scrapedAt": "2026-09-03T20:32:00.000Z"
}
```

#### Field coverage

Measured across 228 rows from two restaurants (Birmingham and Times Square), and a 17-item Hamburgers spot-check with `includeDetails` on:

| Field | Coverage |
|---|---|
| `price`, `calories`, `categoryName` | 100% |
| store address columns (address search) | 100% |
| `description`, `modifiers` (with `includeDetails`) | 100% |

### Pricing

| Event | When it fires | Rate |
|---|---|---|
| Actor start | Once per run | $0.005 |
| Result | Per product row returned | $0.0007 |

A restaurant returns roughly 150 products, so one location runs about $0.11 and a sweep of 10 restaurants about $1.06. Categories, calories and combo flags ride on every row at no extra charge; a store that returns nothing costs nothing.

### What makes this richer than the competition

| Capability | Other Wendy's actors | This actor |
|---|---|---|
| Search by street address | ZIP only | Street address, ZIP, city and restaurant number |
| Batch many locations per run | Limited | Yes, mixed formats in one input |
| Prices specific to the restaurant | Unclear | Yes, proven to differ between stores |
| Calories on every row | Partial | Yes |
| Item descriptions + customisation options | No | Yes, opt-in |
| Full store metadata (hours, phone, coords) | No | Yes |
| Row padding | Same item repeated per category | One row per product |

### Notes & limitations

- **United States only.** The location search and menu this actor reads are the US region.
- **Restaurant numbers return the menu without the address.** Wendy's exposes a restaurant's address only through its location search, so a row that came from `restaurantIds` has `storeAddress`, `storeCity` and coordinates set to `null`. Search by address when you need those columns.
- **Spelling and abbreviations don't matter.** Wendy's own location search geocodes each address, so "Road" vs "Rd" or "West" vs "W" resolve to the same restaurant — the actor never compares your text against Wendy's formatting.
- **Address matching is nearest-restaurant, not exact-match.** Paste a restaurant's own address and you get that restaurant; paste any other address and you get the closest Wendy's to it.
- **Macros and allergens are not returned.** Wendy's carries calories on every item, plus descriptions and customisation options behind `includeDetails`, but does not expose per-item macro grams the way some chains do.

### 🤖 For AI Agents & LLM Apps

**Purpose.** Returns the current menu of a specific Wendy's restaurant in the United States: per-store prices, calories, categories, combo/LTO flags, and optionally item descriptions and customisation options.

**Minimal tested input.**

```json
{ "addresses": ["345 Valley Avenue, Birmingham, AL 35209"], "maxStoresPerAddress": 1 }
```

**Output fields (flat).** `type`, `restaurantId`, `storeName`, `storeAddress`, `storeCity`, `storeState`, `storePostalCode`, `storeCountry`, `storeLatitude`, `storeLongitude`, `storePhone`, `searchedAddress`, `itemId`, `itemName`, `slug`, `categoryId`, `categoryName`, `price`, `currency`, `calories`, `isCombo`, `isLimitedTimeOffer`, `isFreestyle`, `hasRequiredModifiers`, `imageId`, `description`, `modifiers`, `allergens`, `scrapedAt`.

**Behaviour worth knowing.**

- One row per product per restaurant; roughly 150 rows per restaurant.
- `addresses` accepts street addresses, ZIP codes and city names in the same array.
- `searchedAddress` echoes the input string that produced the row, so batch results stay traceable.
- Rows sourced from `restaurantIds` have null address columns.
- `description` and `modifiers` are null unless `includeDetails` is true.
- Prices are US dollars as numbers, never strings.
- No credentials, no proxy and no browser are required.

### ⚠️ Disclaimer

This actor collects publicly available menu information published by Wendy's for its United States restaurants. It does not access private, personal or authenticated data, and it does not attempt to bypass any authentication. Menu content, prices, calorie values and trademarks belong to their respective owners; Wendy's® is a registered trademark of Quality Is Our Recipe, LLC, and this actor is not affiliated with, endorsed by or sponsored by Wendy's. Prices and availability change frequently and by location — treat every row as a snapshot taken at `scrapedAt`, and verify anything you rely on for a purchase or a dietary decision against the restaurant directly. Calorie values are reproduced as published and must not be treated as medical advice. You are responsible for using the output in line with applicable law and Wendy's terms.

### SEO Keywords

wendys menu scraper, wendys prices api, wendys menu data, wendys calories scraper, fast food menu scraper, restaurant menu api, wendys store locator api, menu price monitoring, fast food price tracking, baconator price by location, wendys combo prices, quick service restaurant data, menu item pricing dataset, restaurant price intelligence, store level menu pricing, competitive menu analysis, wendys frosty price, us fast food data, wendys nutrition data, menu extraction api

# Actor input Schema

## `addresses` (type: `array`):

One US location per line. A street address returns the nearest restaurant to it; a ZIP or city does the same. Wendy's own location search geocodes each entry, so spelling and abbreviations ('Road' vs 'Rd', 'West' vs 'W') never matter. Examples: '345 Valley Avenue, Birmingham, AL 35209', '35209', 'Birmingham, AL'.

## `restaurantIds` (type: `array`):

Restaurant numbers, when you already know them (for example '1252'). These skip the location search, so they are the fastest way to target a store — but Wendy's only exposes a restaurant's address through its location search, so rows from a restaurant number carry the menu without the address columns. Use the address field above when you need those.

## `maxStoresPerAddress` (type: `integer`):

How many restaurants to return for each location, nearest first. Leave at 1 for an exact address; raise it to survey an area.

## `searchRadiusMiles` (type: `integer`):

How far from each location to look for a restaurant. Used for addresses, not for restaurant numbers.

## `categories` (type: `array`):

Restrict the scrape to specific menu categories by name, case-insensitive. Leave empty for the whole menu. Valid names include: Hamburgers, Chicken, Nuggets & More, Tenders, Combos, Fresh-Made Salads, Fries & Sides, Frosty®, Beverages, Coffee, Bakery, Biggie Deals®.

## `includeDetails` (type: `boolean`):

Fetch each product's detail page to add its description and the list of customisation options (modifiers). Off by default because it makes one extra request per product; price and calories are on every row without it.

## `maxItems` (type: `integer`):

Hard cap on dataset rows. A restaurant carries roughly 150 products, so 5000 covers about 30 restaurants.

## `maxConcurrency` (type: `integer`):

How many HTTP calls run in parallel. The default suits most runs; lower it only if you hit rate limits.

## `proxy` (type: `object`):

Optional. Wendy's endpoints answer from any IP, so this actor runs without a proxy by default. Supply one only if your network needs it.

## Actor input object example

```json
{
  "addresses": [
    "345 Valley Avenue, Birmingham, AL 35209",
    "10036"
  ],
  "maxStoresPerAddress": 1,
  "searchRadiusMiles": 25,
  "includeDetails": false,
  "maxItems": 5000,
  "maxConcurrency": 8,
  "proxy": {
    "useApifyProxy": 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "addresses": [
        "345 Valley Avenue, Birmingham, AL 35209",
        "10036"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("memo23/wendys-menu-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "addresses": [
        "345 Valley Avenue, Birmingham, AL 35209",
        "10036",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("memo23/wendys-menu-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "addresses": [
    "345 Valley Avenue, Birmingham, AL 35209",
    "10036"
  ]
}' |
apify call memo23/wendys-menu-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,memo23/wendys-menu-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZtPoEbuEWg9XhTiCD/builds/SQIPXoZ4Xy1bhbiGk/openapi.json