MCP Server for Uber Eats Data Extraction

Use Bright Data’s enterprise-grade MCP Server to scrape public Uber Eats data. Extract, analyze, and process public restaurant listings, menus, pricing, delivery fees, ratings, reviews, cuisines, locations, hours, and promotional offers across cities quickly, reliably, and at scale.

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The Ultimate MCP Tool to Scrape Uber Eats Data

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One MCP for the Web

Bright Data MCP for Uber Eats lets you extract public restaurant listings, menus, pricing, delivery fees, ratings, reviews, cuisines, and promotional offers across cities.
Search
  • Enable Claude to retrieve real-time public Uber Eats data for any city, cuisine, or restaurant type worldwide
  • Target specific locations, delivery zones, or cuisine categories for localized restaurant and pricing insights
  • Fetch relevant menus, prices, ratings, delivery fees, and promotional offers for Claude to analyze, compare, or monitor further
Crawl
  • Let Claude crawl and extract complete restaurant profiles, full menus, and customer reviews, not just headline ratings
  • Output public Uber Eats data in Claude-ready formats for seamless LLM integration
  • Effortlessly scale restaurant and menu data extraction for Claude, no matter the project size
Access
  • Give Claude reliable access to any public Uber Eats restaurant listing, menu item, review, or pricing data
  • Bypass geo-restrictions and CAPTCHAs automatically for uninterrupted Uber Eats data extraction by Claude
  • Render JavaScript to retrieve dynamically loaded menus, availability, delivery fees, and promotional offers for Claude's use
Navigate
  • Automate Claude agent workflows to extract Uber Eats data from interactive search results, filters, and restaurant comparison tables
  • Power remote browser sessions for Claude to streamline large-scale restaurant menu and pricing data scraping
  • Mimic real user behavior for Claude to bypass advanced anti-bot protections on Uber Eats
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Uber Eats MCP Server FAQs

The Uber Eats MCP Server is a specialized integration that empowers your AI agents to access real-time public data from Uber Eats. It acts as a bridge, allowing tools like Claude, Cursor, and custom LLMs to search, extract, and interact with Uber Eats content dynamically.

Built on Bright Data's robust infrastructure, the Web MCP Server handles the complexities of web data extraction behind the scenes. It automatically manages proxy rotation, CAPTCHA solving, and unlocking technology to ensure your AI receives structured, reliable data from Uber Eats without getting blocked.

The data is completely real-time. Unlike databases that can become outdated, the Uber Eats MCP fetches live content directly from the source at the moment of request, ensuring your AI agents act on the most current pricing, posts, or profile information available.

Yes! We offer a generous free tier that includes 5,000 requests per month. This allows developers and businesses to test the Uber Eats MCP Server, build prototypes, and perform light data extraction at no cost before scaling up.

Yes. Beyond retrieving static data, the server supports full browser automation. Your agents can be instructed to navigate Uber Eats pages, click buttons, handle infinite scrolling, and even take screenshots, enabling complex workflows that simulate real user behavior.

You have the choice. You can use our fully managed Remote MCP for instant access with zero infrastructure setup, or you can deploy the Local MCP if you require on-premise control and custom environment configurations for your Uber Eats projects.

Our Web MCP Server is designed for seamless integration with popular AI clients. It works natively with Claude Desktop, Cursor, Windsurf, and diverse agentic frameworks like LangChain, making it easy to add Uber Eats data capabilities to your existing workflows.

Rapid mode is free and ideal for everyday tasks like SERP lookups and basic text extraction. Pro mode unlocks premium capabilities for Uber Eats, including deep structured data extraction and advanced browser automation tools designed for large-scale production environments.

Absolutely. The Uber Eats MCP Server is built with strict adherence to data protection regulations, including GDPR and CCPA. We only access publicly available web data, ensuring your AI operations remain compliant and ethically sound.

The server delivers data in clean, AI-ready formats. Depending on your specific needs, you can retrieve Uber Eats data as structured JSON objects for precise analysis or as simplified Markdown text optimized for LLM context windows.