Yandex

@Yandex find coffee shops near Nevsky Prospekt in Saint Petersburg and show me their addresses and ratings

Found 12 coffee shops within 500m of Nevsky Prospekt. Top results: (1) Coffee House — Nevsky Prospekt 28, rating 4.3/5, open until 23:00; (2) Bushe — Nevsky Prospekt 44, rating 4.1/5, bakery-café; (3) Coffeeshop Company — Nevsky Prospekt 114-116, rating 4.2/5. All locations verified via Yandex Maps organization database. Additional details available on request.

This example uses the Organization Search tool to query businesses by location and category. Results depend on Yandex's coverage in the specified region — strongest in Russia and CIS countries. OAuth scope must include maps API access. Search radius and result count are configurable parameters.

@Yandex generate a walking route from the Hermitage Museum to Kazan Cathedral and tell me how long it will take

Route generated: Start at Palace Square (Hermitage), head south on Nevsky Prospekt for 850m, turn right onto Kazanskaya Street. Total distance: 1.1 km, estimated time: 14 minutes walking at average pace. Route includes 2 pedestrian crossings and passes through Gostiny Dvor shopping area. Detailed turn-by-turn directions available with street names and landmarks.

This demonstrates the Generate Detailed Route tool for pedestrian navigation. The MCP calculates time estimates based on typical walking speed and terrain. Driving and public transport modes are also supported. Route quality depends on Yandex's street graph data — most reliable in major Russian cities.

@Yandex what's the exact address and coordinates for the location at 59.9343° N, 30.3351° E, and show me a map tile of that area

Reverse geocoding result: Palace Square, Saint Petersburg, Russia 190000. Coordinates: 59.9343° N, 30.3351° E. This location is in the Tsentralny District, adjacent to the Winter Palace. Map tile retrieved at zoom level 16 (tile coordinates: x=39070, y=19447) showing surrounding streets and landmarks. Tile image available as PNG, suitable for embedding in custom map interfaces.

This pairs the Yandex Geocoder Reverse tool with the Tiles API to convert coordinates into human-readable addresses and visual context. Useful for location verification or building custom map UIs. Tile fetching has rate limits — cache tiles when rendering multiple views. Reverse geocoding accuracy varies by region density.

When Yandex wins for Russia-focused route optimization

A 6-person sales team covering Moscow and St. Petersburg needs to plan weekly territory visits across 40-60 client sites. Yandex's route generation handles Russian address formats and local transit nuances that Google Maps often misses—critical when your reps are navigating Cyrillic street names and marshrutka schedules. The organization search tool pulls business TINs for compliance checks without leaving the planning session. This MCP makes sense if your team operates primarily in Russia or CIS markets and needs OAuth-secured access to Yandex's superior local data. If your territory spans Western Europe or the US, stick with Google Maps integrations—Yandex's coverage drops off sharply outside its home region. For Russia-heavy field ops, this is the routing MCP that actually knows the ground truth.

Reverse geocoding for real-time driver location tracking

A 12-person dispatch team managing last-mile delivery in Yekaterinburg uses driver GPS pings to update customer ETAs every 90 seconds. Yandex's reverse geocoder converts lat-long streams into human-readable addresses faster than parsing Google's responses, and the tile API lets the team render custom delivery zone maps without embedding a full Yandex widget. The 4-tool scope is lean enough that junior dispatchers can ask the AI 'where is driver 14 right now' and get a street address plus a static map snippet in under 2 seconds. This setup works when your delivery radius is under 50km and your address density is high—rural routes with sparse POIs will see slower geocoding. If your dispatch volume exceeds 200 pings per minute, you'll need a dedicated Yandex API contract outside Switchy. For mid-scale urban logistics in Russia, this MCP keeps dispatch moving without custom dev work.

Organization search for competitive landscape mapping

A 3-person strategy team evaluating retail expansion sites in Kazan needs to count competitor density within 2km of each candidate location. Yandex's organization search pulls business names, addresses, and TINs by category—'supermarkets', 'pharmacies', 'coffee shops'—then the geocoder converts those addresses to map pins for density heatmaps. The team runs 8-10 queries per site analysis, asking the AI 'how many grocery stores are within walking distance of this address' and getting structured lists they paste into their site-scoring spreadsheet. This MCP is the right call when your research focuses on Russian cities where Yandex's POI database is 2-3x richer than Western alternatives. If you're comparing sites across multiple countries, you'll need a multi-provider setup—Yandex won't help in Berlin or Boston. For Russia-only market research, this is the fastest path from address to competitive intel.