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Zomato Restaurant Scraper City, Cuisine, Contact

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
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Zomato Restaurant Scraper - City, Cuisine, Contact

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for Zomato Restaurant Scraper - City, Cuisine, Contact, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
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Documentation Overview

Zomato Restaurant Scraper

πŸ“¦ Open source Β· MIT: github.com/AnshumanAtrey/zomato-restaurant-scraper

Scrape restaurant listings from Zomato by city and cuisine. Get structured records with name, phone, address, cuisines, rating, and cost for two β€” no Zomato account required.

Built for B2B sales teams, food-tech researchers, ghost-kitchen operators, lead-gen agencies, and competitor intelligence.

Quick start

  1. Pick a City from the dropdown (Bangalore, Delhi NCR, Mumbai, Dubai, Singapore, etc. β€” 40 cities)
  2. Pick a Listing Type (Best, All, Dinner, Breakfast)
  3. Optionally pick a Cuisine filter (Biryani, Pizza, North Indian, Chinese, etc. β€” 24 options)
  4. Set how many restaurants you want (default 50, up to 1000)
  5. Click Run

Typical 50-restaurant scan completes in 3-7 minutes.

What you get

Each restaurant is pushed as one dataset record:

FieldExample
nameTruffles
urlhttps://www.zomato.com/bangalore/truffles-st-marks-road-central-bangalore/info
slugtruffles-st-marks-road-central-bangalore
phone+91 80 4111 2400
address22, St Marks Road, Bangalore
cuisinesAmerican, Burger, Continental
rating4.5
costForTwoβ‚Ή800
citybangalore
areaCentral Bangalore
timestamp2026-05-22T09:43:18Z

A final summary record reports restaurantsScraped, restaurantsFound, failures, duration, and sourceUrls.

Common use cases

Build a B2B restaurant lead list

Pick Mumbai, Best restaurants, maxRestaurants: 200. Export the CSV. You now have 200 verified phone numbers + addresses for outreach.

Scrape a specific cuisine in a specific city

Pick Hyderabad, All restaurants, Cuisine: Biryani, maxRestaurants: 100.

Scrape a city not in the dropdown

Use the Custom city field under "Advanced overrides". Type Tirunelveli, Erode, Coorg, Manali, Madurai, Varanasi β€” auto-converted to the right Zomato URL.

Scrape a category not in the dropdown

Use the Custom cuisine field. Momos, Kebab, Hyderabadi, Awadhi all work.

Scrape an exact Zomato URL you already have

Paste it into Custom URL under "Advanced overrides". Overrides every other dropdown.

Inputs

Main fields

  • City β€” Pick from 40 Zomato cities across India, UAE, Qatar, Oman, Malaysia, Singapore, Philippines, Sri Lanka, Portugal
  • Listing Type β€” Best restaurants (curated top picks), All restaurants, Dinner spots, or Breakfast spots
  • Cuisine β€” Optional filter across 24 cuisine categories, or "Any" for no filter
  • How many restaurants β€” Cap on results (1-1000). Start with 20-50 to verify, then scale up
  • Scan depth:
    • Quick β€” restaurant URLs + names only (fast, cheap, useful for bulk URL lists)
    • Standard β€” full data: phone, address, rating, cost (default β€” recommended for B2B leads)
    • Deep β€” full data with extra retries for blocked pages (slowest, highest yield)

Advanced overrides (optional)

  • Custom city β€” Type any Zomato city not in the dropdown. Auto-slugified
  • Custom cuisine β€” Type any Zomato cuisine category not in the dropdown
  • Custom URL β€” Paste any Zomato listing URL to scrape it directly. Overrides everything above

Runtime

  • Run timeout (seconds) β€” Hard kill after this many seconds (default 1800 = 30 min)

How it works

  1. Listing page: navigates to the constructed Zomato URL, scrolls to load lazy content, extracts all restaurant detail URLs (handles both /info and /order URL patterns)
  2. Detail pages: visits each restaurant page concurrently using fast HTTP fetches (Cheerio) β€” typically 5-10x faster than full browser rendering
  3. Auto-fallback: if the primary URL returns 0 restaurants, automatically retries /{city}/restaurants as a fallback

Uses Apify Residential Proxy to avoid rate-limit issues.

Pricing

$0.005 per restaurant record. A typical 50-restaurant scan costs ~$0.26.

Scan sizeApprox cost
20 restaurants$0.10
50 restaurants$0.25
100 restaurants$0.50
500 restaurants$2.50
1000 restaurants$5.00

FAQ

Does it scrape menu items / dishes?

No β€” it scrapes restaurant listings (name, phone, address, etc.), not menus. For menu data, use a different actor that hits individual restaurant pages with menu rendering.

Can I scrape "Dahi Puri" or "Tandoor"?

Zomato organizes by cuisine category, not by individual dish. Specific dishes like dahi-puri don't have their own URL on Zomato. Use a broader category like Street Food or North Indian instead.

Can I scrape an entire state like "Tamil Nadu"?

Zomato has no state-level URLs. Pick a specific city instead β€” e.g., for Tamil Nadu use Chennai, Coimbatore, or custom-city Madurai/Tirunelveli.

Does it work for cities outside the dropdown?

Yes. Use the Custom city field with the city name β€” Erode, Coorg, Manali, Varanasi, etc. The actor auto-slugifies and auto-falls-back to /{city}/restaurants if /best-restaurants doesn't exist for that smaller city.

Why didn't I get any results?

Most likely causes:

  • Off-list cuisine combined with quick scan β€” try Standard depth
  • City has no listings for that cuisine β€” try removing the cuisine filter
  • Custom URL is malformed β€” paste it in a browser first to verify

What about international cities?

Dubai, Abu Dhabi, Sharjah (UAE), Doha (Qatar), Muscat (Oman), Kuala Lumpur (Malaysia), Singapore, Manila, Colombo, Lisbon are in the dropdown. Other Zomato international cities (e.g., Sydney, Auckland) work via the Custom city field.

Is the data accurate / fresh?

Pulled live from Zomato at run time. Phone numbers and addresses are exactly what Zomato displays today. Ratings may lag slightly behind Zomato's internal scoring.

Is this legal?

Scrapes only publicly visible data on Zomato. You are responsible for complying with Zomato's Terms of Service, GDPR/DPDP, and local laws. Don't use phone numbers for mass cold-calling without consent.

Output structure

config.json
{
  "recordType": "restaurant",
  "name": "Truffles",
  "url": "https://www.zomato.com/bangalore/truffles-st-marks-road-central-bangalore/info",
  "slug": "truffles-st-marks-road-central-bangalore",
  "phone": "+91 80 4111 2400",
  "address": "22, St Marks Road, Bangalore",
  "cuisines": ["American", "Burger", "Continental"],
  "rating": 4.5,
  "costForTwo": "β‚Ή800",
  "city": "bangalore",
  "area": "Central Bangalore",
  "timestamp": "2026-05-22T09:43:18Z"
}

Plus one summary record per run:

config.json
{
  "recordType": "summary",
  "restaurantsScraped": 50,
  "restaurantsFound": 52,
  "failures": 2,
  "duration": 287,
  "sourceUrls": ["https://www.zomato.com/bangalore/best-restaurants"]
}

Pairs nicely with

Enrich your restaurant lead lists with deeper intel:

  • Holehe Email OSINT β€” After scraping restaurant emails from their websites, check which platforms each restaurant owner is on
  • NetIntel β€” WHOIS, DNS, SSL, GeoIP of each restaurant's website
  • Social Analyzer β€” Find a restaurant brand's social media presence across 900+ platforms
  • theHarvester β€” Discover all subdomains + emails for a restaurant chain's primary domain
  • nmap β€” Network recon (for IT/security workflows, not lead-gen)
  • Bug Bounty Finder β€” Audit a restaurant chain's disclosure-program coverage

Credits

Built by Anshuman Atrey using Apify SDK, Crawlee, Puppeteer, and Cheerio.

Disclaimer

This scraper accesses publicly available data on Zomato. You are responsible for complying with Zomato's Terms of Service and applicable laws in your jurisdiction. Use the data responsibly β€” avoid mass cold-calling without consent.

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Zomato Restaurant Scraper City, Cuisine, Contact

We don't have a confirmed install command for Zomato Restaurant Scraper - City, Cuisine, Contact yet, so we don't publish a generated one β€” a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/AnshumanAtrey/zomato-restaurant-scraper) for the current steps.

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Technical Specs & Signals

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Last updatedSep 28, 2026
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Verified ownership8/20
Documentation & tools10/30
Adoption & activity1/15
Community engagement0/10

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