Tabelog Japan Scraper - Restaurants, Ratings, Menus & Reviews

Scrape restaurants from Tabelog (tabelog.com), Japan's largest restaurant guide. Search by cuisine and a plain area name such as Shibuya or Osaka, or paste any Tabelog link, and get rating, review count, genre, nearest station, lunch and dinner budget, closed days, smoking policy, photos and online reservation availability for every restaurant, plus address, business hours, payment methods, seats and the newest reviews.

Why This Scraper?

• Two ways in. Search by keyword and area name (Shibuya, Akihabara, Osaka, Sapporo), or paste any Tabelog link: restaurant, review, menu or photo page, search list, area page or cuisine list.
• Ranked the way Tabelog ranks. Keep the site ranking, or sort by highest rating or most reviews.
• Useful filters. Minimum rating, minimum reviews, smoking policy and online-reservation-only.
• Budgets as numbers and text. Lunch and dinner budget come as the shown range plus minimum and maximum yen values.
• Reservation availability. Restaurants that take online reservations carry the upcoming days and their status, one flat record per restaurant with no duplicates.
• Optional details. Turn on restaurant details to add address, postal code, coordinates, phone number, business hours, payment methods, seats, private rooms, parking, transportation, facilities and occasions.
• Reviews on the row. The newest reviews (20 by default) ride the restaurant record with reviewer, rating, meal time, sub scores, spend, visit month, text and photos. Turn on full review text to open each cut-off review.

Use Cases

• Food and travel apps: build restaurant directories with ratings, stations and budgets.
• Market research: compare cuisines, price bands and review volume across Japanese cities.
• Hospitality analysts: track top ranked restaurants and awards in an area over time.
• Lead generation: list restaurants by area with address and phone number.
• Reputation tracking: follow what diners say about a restaurant through its newest reviews.
• Tour planners: find non smoking, reservable restaurants near a station.

Data You Get

Sample shape: values are illustrative placeholders, not from a live record.

Field	Example
restaurantId	13000000
name	Sample Ramen Shop
rank	1
rating	3.60
reviewCount	500
genre	Ramen, Tsukemen (Dipping noodles)
station	Sample Sta.
stationDistance	250m
dinnerBudget	- JPY 999
lunchBudget	JPY 1,000 - JPY 1,999
closedDays	Sunday, Public Holiday
smokingPolicy	Non smoking
imageUrl	https://example.com/photo.jpg
reservation	true
reservationInfo	{"onlineReservation": true, "days": [...]}
address	Sample district, Tokyo
latitude / longitude	35.0 / 139.0
phone	+81-0-0000-0000
url	https://example.com/restaurant/
businessHours	Mon-Fri 11:00 AM - 2:30 PM
paymentMethods	Credit cards not accepted
seats	12 seats (12 counter seats)
transportation	Sample Line, Sample Station, 1 minute walk
reviews	list of review objects (see below)
reviewsDelivered	20

Review object (inside reviews):

Sample shape: values are illustrative placeholders, not from a live record.

{
  "reviewId": "B500000000",
  "reviewUrl": "https://example.com/review/",
  "reviewerName": "Sample reviewer",
  "reviewerPostCount": 120,
  "rating": 3.5,
  "mealTime": "lunch",
  "scoreFood": 3.5,
  "scoreService": null,
  "spendPerPerson": "JPY 1,000～JPY 1,999",
  "visitMonth": "2026-10",
  "visitCount": 1,
  "title": "Sample title",
  "text": "Sample review text",
  "textTruncated": false,
  "photos": []
}

How to Use

1. Pick a mode: search by keyword and area, or paste Tabelog links.
2. Set your keywords, areas and filters, or paste the links.
3. Choose Max items, whether to add restaurant details and how many reviews to attach.
4. Run it and download the dataset as JSON, CSV or Excel.

Search ramen in Tokyo:

{
  "mode": "search",
  "searchTerms": ["ramen"],
  "locations": ["tokyo"],
  "maxItems": 20
}

Top rated sushi in two cities with details:

{
  "mode": "search",
  "searchTerms": ["sushi"],
  "locations": ["tokyo", "osaka"],
  "sortBy": "rating",
  "minReviews": 100,
  "fetchDetails": true,
  "maxItems": 50
}

Search by plain area name:

{
  "mode": "search",
  "searchTerms": ["yakiniku"],
  "locations": ["Shibuya", "Osaka"],
  "maxItems": 30
}

Paste links of any shape:

{
  "mode": "url",
  "urls": [
    "https://tabelog.com/en/tokyo/A1310/A131002/13011452/",
    "https://tabelog.com/en/tokyo/rstLst/?sw=ramen",
    "https://tabelog.com/en/tokyo/A1303/",
    "https://tabelog.com/en/rstLst/ramen/"
  ],
  "maxItems": 40,
  "maxReviews": 20
}

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("<ACTOR_ID>").call(run_input={"mode": "search", "searchTerms": ["ramen"], "locations": ["tokyo"], "maxItems": 20})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["name"], item["rating"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('<ACTOR_ID>').call({ mode: 'search', searchTerms: ['ramen'], locations: ['tokyo'], maxItems: 20 });
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.map((i) => `${i.name} ${i.rating}`));

Tips

• Type areas as plain names: a prefecture (Tokyo, Osaka, Kyoto) or an area (Shibuya, Akihabara, Ginza, Sapporo, Nagoya). Area codes such as A1310 and paths such as tokyo/A1310 also work, and all searches the whole country. A name that cannot be matched is named in the log and skipped, never guessed.
• Reviews are read for every restaurant whose own page is read: with Add restaurant details on, or for a restaurant link pasted in URL mode. Set Max reviews per restaurant to 0 to skip them.
• Max items is the cap for the whole run and is shared across every keyword and area. Max pages does not cap the run.
• Leave search keywords empty to list every restaurant in an area.

Send results into your apps (MCP connectors)

Optionally send the scraped results into the apps you already use via Model Context Protocol (MCP) connectors. Authorize a connector once under Apify, Settings, Integrations, then select it in the run input. The connector receives a short summary per item; the full record stays in the dataset. Leave the field empty to skip.

Input Parameters

Parameter	Type	Default	Description
mode	string	search	Search by keyword and area, or paste Tabelog links.
searchTerms	array	["ramen"]	Cuisine, dish or restaurant name. Empty lists every restaurant in the area.
locations	array	["Tokyo"]	Plain area names (Shibuya, Osaka), area codes or paths such as tokyo/A1310; all for the whole country.
sortBy	string	ranking	Tabelog ranking, highest rating or most reviews. Most reviews orders the first 10 list pages (about 200 restaurants) of each search.
minRating	number	0	Keep restaurants rated at least this value.
minReviews	integer	0	Keep restaurants with at least this many reviews.
smoking	string	any	Any, non smoking, designated area, smoking allowed or heated tobacco only.
reservableOnly	boolean	false	Keep only restaurants that take online reservations.
urls	array	five sample links	Restaurant, review, menu or photo pages, search lists, area pages and cuisine lists. Filter fields are ignored.
fetchDetails	boolean	false	Add address, postal code, coordinates, phone, business hours, payment methods, seats and more, plus reviews.
maxReviews	integer	20	Newest reviews attached to each restaurant whose page is read. 0 skips reviews.
fullReviewText	boolean	false	Open each cut-off review for its complete text.
maxPages	integer	empty	Page limit per search. Does not cap the run.
maxItems	integer	20	Maximum restaurants for the whole run. 0 means unlimited.
proxy	object	Apify proxy	Proxy settings.
resumeFromRunId	string	empty	Run or dataset id of an earlier run. Restaurants collected there are skipped.
incrementalMode	boolean	false	Return only NEW, UPDATED and REAPPEARED restaurants on repeat runs.
stateKey	string	empty	Name a monitoring campaign to keep its state stable.
emitUnchanged	boolean	false	Also return restaurants that did not change.
emitExpired	boolean	false	Also return restaurants no longer found after a complete scan.
ignoreFieldsForChanges	array	empty	Field names whose changes alone do not mark a restaurant UPDATED.
mcpConnectors	array	empty	Optional connectors to send results to.
notionParentPageUrl	string	empty	Notion page under which item pages are created.
maxNotifyListings	integer	50	Cap on items exported per connector.

Output Example

Sample shape: values are illustrative placeholders, not from a live record.

{
  "recordType": "restaurant",
  "restaurantId": "13000000",
  "name": "Sample Ramen Shop",
  "rank": 1,
  "rating": 3.6,
  "reviewCount": 500,
  "genre": "Ramen, Tsukemen (Dipping noodles)",
  "station": "Sample Sta.",
  "stationDistance": "250m",
  "dinnerBudget": "- JPY 999",
  "lunchBudget": "JPY 1,000 - JPY 1,999",
  "closedDays": "Sunday, Public Holiday",
  "smokingPolicy": "Non smoking",
  "reservation": false,
  "detailsScraped": false,
  "scrapedAt": "2026-01-01T00:00:00Z"
}

Plan Requirement

The actor runs on any Apify plan. Proxy usage is billed by Apify according to your plan.

Proxy

The default Apify proxy reads this site reliably and works on every plan that includes proxy access. Residential is recommended for the most reliable results on large or frequent runs. If a connection type is refused for your account, the run continues on a backup connection and logs a notice. Apify free plans do not include residential proxies, so some pages may be unavailable there; upgrade at https://apify.com/pricing or supply your own proxy URLs. Residential traffic is capped per run, after which the run continues on the standard connection.

FAQ

How much does a run cost?

You pay per restaurant returned, a detail event per restaurant whose own page is read, and a review event for each review delivered on those restaurants. Restaurants that are not returned, unchanged restaurants hidden by incremental mode and reviews that were not delivered are never charged. See the pricing tab for the current rates.

Is it legal to scrape Tabelog?

The actor reads publicly visible restaurant information. You are responsible for using the data in line with the site terms and the laws that apply to you.

Can I schedule runs?

Yes. Use Apify schedules to refresh a search daily or weekly.

Why are some budgets empty?

Restaurants that list no lunch or dinner budget return an empty value.

Why did a run fail?

A run fails only when no page could be read at all. Try again later or choose a different proxy group.

Can I use it with AI tools?

Yes. Use the MCP export or the Apify MCP server to hand results to your assistant.

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