Yelp Business Profile, Hours & Menu Extractor: MCP config, n8n workflow and API

{
  "searchTerms": [
    "pizza"
  ],
  "locations": [
    "New York, NY"
  ],
  "searchLimit": 3,
  "reviewLimit": 3,
  "fetchPhotos": true,
  "fetchHours": true,
  "fetchMenu": false,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}

---
name: yelp-business-profile-hours-and-menu-extractor
description: "Dataset of Yelp business records with hours, services, menu, photos by category, owner replies, coordinates, claim status, and reviews. Runs the Apify Actor dataspryva/yelp-business-profile-hours-and-menu-extractor. Use when the user needs Yelp data with fields such as name, aggregatedRating, reviewCount, priceRange, phone, claimStatus and an Apify token is available."
compatibility: "Needs network access, curl, and an APIFY_TOKEN environment variable. Runs are billed to the token owner's Apify account."
metadata:
  actor: "dataspryva/yelp-business-profile-hours-and-menu-extractor"
  store-url: "https://apify.com/dataspryva/yelp-business-profile-hours-and-menu-extractor"
---

# Yelp Business Profile, Hours & Menu Extractor

Use this skill to fetch Yelp data with the Apify Actor `dataspryva/yelp-business-profile-hours-and-menu-extractor` and work with the returned rows.

## Before running

1. Check that `APIFY_TOKEN` is set in the environment. Never print it or write it to a file.
2. Build `input.json` from the user's request using the fields below. Keep limits small for a first run.
3. Confirm the search terms or URLs with the user if the request is ambiguous.

## Input fields

| Field | Type | Meaning |
| --- | --- | --- |
| `searchTerms` | array | List of search queries (e.g., 'pizza', 'plumber', 'hair salon'). Used together with Locations to find businesses on Yelp. |
| `locations` | array | List of locations to search in (e.g., 'New York, NY', 'Los Angeles, CA'). Each search term is combined with each location. |
| `searchLimit` | integer | Maximum number of business results to collect per search query. Lower values mean faster runs. |
| `reviewLimit` | integer | Maximum number of reviews to collect per business. Set to 0 to skip review extraction. Yelp publicly exposes approximately 30 reviews per business. |
| `fetchPhotos` | boolean | Extract all gallery photos grouped by category (food, inside, outside, menu) when available. |
| `fetchHours` | boolean | Extract hours of operation for each day of the week. |
| `fetchMenu` | boolean | Attempt to extract menu items for restaurants. Adds one extra request per business. Yelp's menu feature is US-only and not available for every restaurant. |
| `proxy` | object, required | REQUIRED. Yelp uses Cloudflare protection. Residential proxy is mandatory; datacenter IPs are reliably blocked. |

Example `input.json` (the Actor's published prefill):

```json
{
  "searchTerms": [
    "pizza"
  ],
  "locations": [
    "New York, NY"
  ],
  "searchLimit": 3,
  "reviewLimit": 3,
  "fetchPhotos": true,
  "fetchHours": true,
  "fetchMenu": false,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

## Run

```bash
curl -sS -X POST "https://api.apify.com/v2/acts/dataspryva~yelp-business-profile-hours-and-menu-extractor/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d @input.json > results.json
```

The call waits for the run to finish and returns the dataset items as a JSON array. If the run needs more than 300 seconds the API answers with HTTP 408; then start the run with `POST /v2/acts/dataspryva~yelp-business-profile-hours-and-menu-extractor/runs`, poll `GET /v2/actor-runs/{runId}` until `SUCCEEDED`, and read `GET /v2/datasets/{defaultDatasetId}/items`.

## Output

Each item is one record. Published fields include: `name`, `aggregatedRating`, `reviewCount`, `priceRange`, `phone`, `claimStatus`, `address`, `directUrl`, `bizId`, `description`, `categories`, `type`, `cuisine`, `website`, `images`, `coordinates`, `hours`, `services`, `photoCategories`, `menu`.

Summarise what was found, cite the record URLs when present, and say how many items came back. Do not invent values for empty fields.