# Uber Eats Mexico City Taqueria Discovery

**Use case:** 

Discover taquerias delivering across Roma, Polanco and Centro Historico in Mexico City on Uber Eats, with ratings, review counts and delivery estimates.

## Input

```json
{
  "locations": [
    "Av. Alvaro Obregon 99, Roma Nte., Cuauhtemoc, 06700 Ciudad de Mexico, CDMX, Mexico",
    "Av. Presidente Masaryk 111, Polanco, Miguel Hidalgo, 11560 Ciudad de Mexico, CDMX, Mexico",
    "Eje Central Lazaro Cardenas 2, Centro Historico, Cuauhtemoc, 06000 Ciudad de Mexico, CDMX, Mexico"
  ],
  "search_keyword": "Tacos",
  "max_search_results": 50
}
```

## Output

```json
{
  "store_uuid": {
    "label": "Store UUID",
    "format": "string"
  },
  "name": {
    "label": "Store Name",
    "format": "string"
  },
  "url": {
    "label": "Store URL",
    "format": "url"
  },
  "city": {
    "label": "City",
    "format": "string"
  },
  "country_code": {
    "label": "Country Code",
    "format": "string"
  },
  "estimated_time_to_delivery": {
    "label": "Estimated Time to Delivery",
    "format": "string"
  },
  "rating": {
    "label": "Rating",
    "format": "number"
  },
  "rating_count": {
    "label": "Rating Count",
    "format": "string"
  },
  "images": {
    "label": "Store Images",
    "format": "array"
  },
  "extraction_date": {
    "label": "Extraction Date",
    "format": "string"
  },
  "extraction_datetime": {
    "label": "Extraction Datetime",
    "format": "string"
  },
  "input": {
    "label": "Input",
    "format": "object"
  }
}
```

## About this Actor

This example demonstrates how to use [Ubereats Stores Search By Location And Keyword](https://apify.com/datacach/ubereats-stores-search-by-location-and-keyword) with a specific input configuration. Visit the [Actor detail page](https://apify.com/datacach/ubereats-stores-search-by-location-and-keyword) to learn more, explore other use cases, and run it yourself.


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This Task's input is already configured above — use it as-is rather than inventing a new one.

- **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).
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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/datacach/ubereats-stores-search-by-location-and-keyword.md

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).
