# Moscow Sport MCP for local facilities. AI Agent Connect > Moscow Sport MCP gives your AI client direct access to Moscow's physical sports landscape. It maps over 1,000 fitness clubs, 4,000 pitches, hundreds of pools, and major stadiums. Whether you need a floodlit soccer pitch, an indoor pool, or a playground for kids, your agent can pull real-time data on locations, surfaces, and operating hours. ## Overview - **Category:** sports-fitness - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_iT33KrfLdKjBJq2o1iDQbvgzGMuMlnj5cF4KVcZG/ai-agent-connect - **Tags:** moscow, russia, sport, stadiums, swimming, football, fitness, ice-rinks, openstreetmap, wikipedia, keyless ## Description You can use this MCP to navigate the massive sports infrastructure of Moscow. Instead of searching through messy maps, you ask your AI client for specific facilities like indoor swimming pools or outdoor basketball courts. It pulls data from OpenStreetMap and Russian Wikipedia to give you precise locations, surface types, and even stadium histories. If you are looking for a place to train, you can filter by sport, lighting, or whether a facility is open right now. It works for everything from finding a quick running track to locating major arenas like Luzhniki. You can even use it to get a high-level overview of how many sports facilities exist in a specific district. ## Tools ### find_ice_rinks_and_ski Locate Moscow ice rinks and ski bases. You can filter by name or narrow your search to a specific neighborhood using coordinates. ### find_pitches Find outdoor pitches and courts across the city. Use filters for specific sports, surface types, or the presence of floodlighting. ### find_playgrounds Search for children's playgrounds. This tool provides a density map of locations around a specific address. ### find_sport_centres Identify fitness clubs and sports centers. You can filter these by sport type, name, or current opening status. ### find_stadiums Locate major stadiums and arenas like CSKA or Dynamo. Results include sport tags, capacity, and location data. ### find_swimming_pools Find swimming pools in Moscow. You can specify if you need an indoor or outdoor pool and check their operating hours. ### sport_profile Get a citywide summary of sports infrastructure. This provides counts for all facility types in a single request. ### stadiums_wiki Access encyclopedic details about Moscow stadiums. It pulls capacity, opening years, and home club info from Wikipedia. ## Prompt Examples **Prompt:** ``` Is there a floodlit football pitch near me? ``` **Response:** ``` find_pitches with sport: "soccer", lit: "yes" and your coordinates returns the mapped pitches with surface and lighting. ``` **Prompt:** ``` Where can I swim indoors right now? ``` **Response:** ``` find_swimming_pools with covered: "yes" lists the indoor pools with hours; add open_now: "true" when the tool supports it for the moment-of-call check. ``` **Prompt:** ``` Tell me about the Luzhniki stadium. ``` **Response:** ``` find_stadiums with name: "Лужники" locates the arena; stadiums_wiki with detail: "true" adds the Wikipedia entry for the first listed stadium. ``` ## Capabilities ### Facility Discovery Your agent finds specific gyms, pools, or courts based on your current location. ### Attribute Filtering The AI filters results by surface type, lighting, or indoor/outdoor status. ### Infrastructure Auditing Your agent calculates the density of sports facilities in a specific district. ### Historical Research The AI pulls stadium capacities and histories from Wikipedia. ### Real-time Availability Your agent checks if a facility is currently open based on mapped hours. ## Use Cases ### Finding Night Training Spots Ask your agent for soccer pitches with floodlighting to plan an evening match. ### Planning Family Outings Use the playground tool to find play areas near a specific address. ### Checking Pool Access Find indoor swimming pools that are currently open for a quick swim. ### Stadium Fact-Checking Get the capacity and home club of a major arena using the Wikipedia integration. ## Benefits - Eliminates manual searching through multiple map layers. - Provides specific technical details like pitch surface and lighting. - Combines OpenStreetMap data with Wikipedia facts in one interface. - Allows for quick district-wide facility counts. ## How It Works Connecting to this MCP gives your AI client immediate access to Moscow's sports database. 1. Connect your client to Vinkius. 2. Select the Moscow Sport MCP from the catalog. 3. Ask your AI client a specific question about Moscow sports facilities. 4. The agent calls the relevant tool to fetch data from OSM or Wikipedia. 5. Your agent presents the location, hours, or details directly in your chat. ## Frequently Asked Questions **How accurate is the playground data?** Most playgrounds are unnamed in the database. The tool works best as a density map to show you where playgrounds are located around an address. **Can I find outdoor sports at night?** Yes. You can use the find_pitches tool and filter for facilities that have floodlighting. **Does this include major stadiums?** Yes. It includes major arenas like Luzhniki, CSKA, and Dynamo. **Can I check if a pool is indoor or outdoor?** Yes. The find_swimming_pools tool allows you to filter by whether the pool is covered. **What if I need historical info on a stadium?** Use the stadiums_wiki tool to get capacity, opening years, and home club information. **Do I need an API key?** No. Every source is keyless and global: OpenStreetMap (Overpass + Nominatim) and Russian Wikipedia. The MCP defines no credentials. **Why does the Wikipedia roll matter for stadiums?** OSM gives the location and the sport tags; Wikipedia carries the capacity, the opening year and the home club — none of which the map tags reliably hold. **Why are the counts bigger than the rows I get?** Yes. OSM maps most large venues as areas (stadiums, monastery enclosures, university campuses), and every list tool uses the nwr selector, so nodes, ways and relations all count. **Can I find a gym near me?** Pass lat + lon (and optionally km, 0.1–25) and the query narrows to a radius instead of the whole city. Do it before a long list — a citywide scan is capped at 200 rows.