Yandex Maps Scraper - Businesses, Places & Leads
Pricing
from $1.80 / 1,000 business records
Scrape Yandex Maps businesses and places by keyword or URL for lead generation, research and market analysis. Парсер Яндекс Карт: сбор данных о компаниях и местах по запросу или ссылке для поиска клиентов, исследований и анализа рынка.
Search queries to run on Yandex Maps.
[ "restaurants"]Direct Yandex Maps targets - one per row: business page (with or without slug, .com, .ru or m. mobile host, a ?ol=biz&oid= link, or its /reviews/ tab), a ?text= search URL, a city search /maps/{geoId}/{city}/search/{query}/ (percent-encoded queries and ?page=N supported) or a city category page /maps/{geoId}/{city}/category/{rubric}/. Unsupported shapes (short /maps/-/ share links, /maps/search/{query}/ without a city id) are skipped with a warning. The default scrapes one example of each shape.
[ { "url": "https://yandex.com/maps/org/no_plates_coffee/124606085044/" }, { "url": "https://yandex.com/maps/org/124606085044/" }, { "url": "https://yandex.com/maps/org/no_plates_coffee/124606085044/reviews/" }, { "url": "https://yandex.ru/maps/org/no_plates_coffee/124606085044/" }, { "url": "https://yandex.com/maps/?ll=-74.006%2C40.7128&z=12&text=coffee" }, { "url": "https://yandex.com/maps/?text=restaurants" }, { "url": "https://yandex.com/maps/202/new-york/search/restaurants/" }, { "url": "https://yandex.com/maps/202/new-york/category/coffee_shop/" }, { "url": "https://yandex.com/maps/?ol=biz&oid=1018907821" }, { "url": "https://yandex.com/maps/213/moscow/search/%D0%BA%D0%BE%D1%84%D0%B5/" }, { "url": "https://yandex.com/maps/213/moscow/search/coffee/?page=2" }, { "url": "https://m.yandex.com/maps/org/192990200894/" }]Free-text region for keyword searches (resolved to map coordinates via the open OpenStreetMap geocoder). Ignored by startUrls.
Native Yandex Maps filters applied to keyword searches and to search / category / ?text= URLs that do not already carry their own filter. One per row: "good_place" (yes/no filter), "wi_fi", "open_now", or "type_cuisine:italian_cuisine,japanese_cuisine" (list filter with one or more values). Several rows combine. Available ids depend on the category (restaurants offer good_place, wi_fi, business_lunch, takeaway, type_cuisine and more). A filter Yandex does not apply is reported in the run log. Leave empty for no filtering.
Maximum businesses to save per search.
SERP pages walked per search (25 businesses each). 0 = no page cap - Max results per search is the only cap that stops a walk early.
Include the matched raw Yandex response object in each dataset row for debugging.
Open each business page and read its reviews, opening hours and photo totals. Turn OFF for fast, search-card-only rows
Per-business review count when details mode is on. Billing scales with volume: the detail-enrichment surcharge bills 1 unit per enriched row plus 1 unit per started block of 10 reviews (10 reviews = 1 extra unit, 25 = 3, 1000 = 101) - heavy review pulls bill their transfer.
Photos to list per business (id, url, size, tags, credit) when details mode is on. 0 = off. Adds one read per business, included in the existing detail-enrichment unit; no extra charge.
Owner posts and events to list per business (text, publication time, photos) when details mode is on. 0 = off. Adds one or more reads per business, included in the existing detail-enrichment unit; no extra charge.
Read the business menu tab and return the whole menu (all categories, prices, volumes, photos, source, last update) instead of the popular-items preview on the card. Restaurants and shops that publish a menu only. Adds about 0.8 MB of page transfer per business with a menu; included in the existing detail-enrichment unit, no extra charge.
For businesses that belong to a chain, add how many branches the chain has in the same city (one chain page read of about 1.8 MB per distinct chain per run). Included in the existing detail-enrichment unit, no extra charge.
Apify Proxy settings used for all requests. Datacenter (no group) by default; pick RESIDENTIAL when the datacenter pool is refused.
{ "useApifyProxy": true}Paste a previous run ID or dataset ID to continue a full-catalogue walk across separate runs. Businesses already collected there (matched by business id) are skipped, so this run only saves the new ones. Leave empty for a normal fresh run. Distinct from Incremental mode below — this continues one specific interrupted run, not recurring monitoring.
When ON, this actor remembers the previous run of the SAME search (see State key) and classifies each business as NEW / UPDATED / UNCHANGED / REAPPEARED / EXPIRED. UNCHANGED and EXPIRED rows are not saved to the dataset unless enabled below — this is what keeps a scheduled recurring run cheap. Default OFF (every run returns every business, as today). Combining with Resume from a previous run above is only safe on the very first incremental run (no baseline yet) — once a baseline exists, remove Resume from a previous run or set a different State key.
Manually name the incremental baseline for this search, e.g. "nyc-coffee". Leave empty to auto-derive one from the search settings — two runs with the exact same search settings then share a baseline automatically. Set this explicitly if you want to run several DIFFERENT search configs against the SAME named baseline, or keep configs that happen to match fully separate.
When ON, incremental mode also saves businesses with no detected change (changeType="UNCHANGED") to the dataset, instead of only NEW/UPDATED/REAPPEARED. This returns — and bills for — every business every run, defeating the point of incremental mode for most use cases. Default OFF.
When ON, incremental mode also saves a row (changeType="EXPIRED") for each previously-tracked business that no longer appears, once this run reaches the natural end of the search results (skipped on a capped, resumed, or otherwise incomplete run — those cannot tell "gone" apart from "not reached yet"). This returns — and bills for — an extra row per disappeared business. Default OFF.
Field names that must NOT count as a change in incremental mode, e.g. photosCount or addressParts.street (dotted paths reach nested fields, including inside lists). Ignored fields stay in the output rows; they just never turn an unchanged business into UPDATED and never appear in changedFields. Already ignored by default: scrapedAt, rank, raw, searchString, reviews (use reviewsCount to detect new reviews), trafficHistogram, photoUrls, logoUrl.
[]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 here. The connector receives a condensed, human-readable summary per business (title + key fields), not the full JSON — the complete record stays in the dataset. Leave empty to skip. Supported: Notion (https://mcp.notion.com/mcp), Linear (https://mcp.linear.app/sse), Airtable (https://mcp.airtable.com/mcp), Apify (https://mcp.apify.com).
URL (or id) of the Notion page under which item pages are created. Required to enable the Notion export; ignored by other connectors.