ubereats

Scrapes Uber Eats category pages for store listings using curl and cheerio.

5|Updated Apr 9, 2026
One-click install
npx skills add https://github.com/AgentComputerAI/torch --skill ubereats
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ubereats
Source: https://github.com/AgentComputerAI/torch/tree/main/skills/sites/ubereats
Command: npx skills add https://github.com/AgentComputerAI/torch --skill ubereats

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Scraping Uber Eats category pages is difficult because of Cloudflare headers and a massive CSP header that breaks standard Node fetch calls; this skill provides a reliable, no‑browser method to retrieve complete store listings.

Core Features & Use Cases

  • Zero‑browser extraction: Uses curl to download fully rendered HTML without headless browsers.
  • Pagination handling: Automatically iterates through all pages until no stores remain.
  • Robust parsing: Extracts store name, URL, ETA, price tier, promo, image, and IDs using cheerio.
  • CSP overflow workaround: Bypasses Node fetch header limits by executing curl.

Quick Start

Retrieve store listings from a Uber Eats category page by providing its URL to the ubereats skill.

Frequently Asked Questions about ubereats

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I scrape Uber Eats category pages when Node fetch fails due to CSP header limits?

Scraping Uber Eats category pages bypasses Node fetch CSP header limits by executing curl to download fully rendered HTML. This approach avoids headless browsers while reliably retrieving complete store listings despite Cloudflare protections.

What data fields can I extract from Uber Eats store listings?

Extracting Uber Eats store listings yields store name, URL, ETA, price tier, promotional text, image, and unique IDs. Parsing the downloaded HTML with cheerio provides reliable extraction of these specific details from any category page.

Does this scraping method handle pagination across multiple Uber Eats category pages?

Handling pagination automatically iterates through all available Uber Eats category pages. The scraping process continues to collect store data until no further stores remain on the subsequent pages, ensuring complete data extraction.

Why does standard Node fetch break when scraping Uber Eats?

Standard Node fetch breaks when scraping Uber Eats because the site returns a massive Content Security Policy (CSP) header that exceeds Node's processing limits. Cloudflare protections also interfere with standard requests, making curl necessary for retrieval.

Do I need a headless browser to extract store details from ubereats.com?

You do not need a headless browser to extract store details from ubereats.com. Using curl to fetch the HTML and cheerio to parse the resulting document reliably collects store data in a lightweight, zero-browser environment.