# Moscow Sights, Landmarks & Views AI Agent Connect > Moscow Sights, Landmarks & Views MCP gives your AI client access to a massive dataset of 1,500 attractions, 90 viewpoints, and 230 fountains across Moscow. It provides walking-distance lists, real-time opening status, and curated Wikipedia landmark data to help you navigate the city without a guide. ## Overview - **Category:** travel - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_H5QGVaQH9kUtifVur4HgOkeeOoynbnXLphyqokVE/ai-agent-connect - **Tags:** moscow, russia, attractions, landmarks, viewpoints, fountains, sightseeing, openstreetmap, wikipedia, keyless ## Description You can use this MCP to turn your AI agent into a local Moscow expert. Instead of searching through generic travel blogs, you get direct access to mapped coordinates, opening hours, and fee information for thousands of sites. If you are standing in a specific neighborhood and want to know what is worth seeing within a short walk, the MCP pulls a ranked list of nearby attractions, artworks, and viewpoints based on your exact location. It covers everything from the high decks of the Ostankino tower to the various water features and fountains scattered throughout the city. You can even pull a citywide profile to see how many museums or theaters are available in a specific district. It is a practical way to handle the logistics of sightseeing, whether you are looking for a free afternoon activity or a specific landmark mentioned in a history book. ## Tools ### find_attractions Find Moscow attractions using name fragments, location, or current opening status. It returns coordinates, descriptions, and whether entry is free or paid. ### find_fountains Locate Moscow fountains and water features by name or neighborhood. This tool excludes drinking water springs to focus on decorative water features. ### find_viewpoints Identify panorama platforms and viewpoints like Sparrow Hills. It provides names, descriptions, and coordinates for every location. ### moscow_landmarks Access a curated list of Moscow landmarks pulled from Russian Wikipedia. You can request a short encyclopedic summary for the first landmark in the list. ### sights_nearby Get a shortlist of attractions, viewpoints, and artworks within a specific walking radius of your coordinates. ### tourism_profile Get a high-level count of all mapped attractions, fountains, museums, and theaters across the entire city. ## Prompt Examples **Prompt:** ``` What can I see within a 2 km walk from Red Square? ``` **Response:** ``` sights_nearby with the Red Square coordinates and km: "2" returns a ranked shortlist with the distance for each sight. ``` **Prompt:** ``` Are there any free attractions open right now? ``` **Response:** ``` find_attractions with fee: "no" and open_now: "true" returns only the free sites that are currently open. ``` **Prompt:** ``` How many fountains are there in Moscow? ``` **Response:** ``` tourism_profile returns the citywide count of approximately 230 mapped fountains. ``` ## Capabilities ### Proximity Searching Your agent finds sights within a specific walking radius of your current location. ### Real-time Status Checks The AI filters attractions to show only those that are currently open to the public. ### Landmark Research Your client pulls historical context and summaries from Wikipedia for specific Moscow landmarks. ### Citywide Data Profiling The agent calculates the total number of museums, fountains, or theaters in the city. ### Visual Point Discovery The AI identifies specific platforms and hills used for city panoramas and views. ## Use Cases ### Spontaneous Walking Tours Ask your agent for sights within a 2 km radius to plan a walk from your current position. ### Budget Sightseeing Filter for free attractions that are open right now to save money and time. ### Finding Scenic Views Locate specific panorama platforms like the Ostankino decks for photography or sightseeing. ### Quick Fact Checking Get historical context for a landmark using the Wikipedia integration. ## Benefits - Access 1,500 mapped attractions without manual searching. - Filter by entry fees to find free activities instantly. - Get precise coordinates for every viewpoint and fountain. - Use Wikipedia summaries to learn about landmarks on the fly. ## How It Works The MCP connects your AI client to OpenStreetMap and Wikipedia data for Moscow. 1. Connect your MCP-compatible client to Vinkius. 2. Ask your AI agent a question about Moscow sights or locations. 3. The agent calls the specific tool needed to fetch the data. 4. The data is returned to your agent as a structured list or summary. 5. Your agent presents the final answer or walking route to you. ## Frequently Asked Questions **How many attractions are in the database?** The MCP includes data for about 1,500 attractions, 90 viewpoints, and 230 fountains. **Can I find free things to do?** Yes, you can use the find_attractions tool and filter for items where the fee is marked as no. **Does this include museums?** This MCP covers a broad list of attractions including museums, though specific cultural deep-dives may require a different tool. **Is the data real-time?** The tool can check if an attraction is open right now based on its recorded operating hours. **How does it handle walking distances?** The sights_nearby tool uses your coordinates to provide a ranked list of sights within a specific radius. **Do I need an API key?** No. Every source is keyless and global: OpenStreetMap (Overpass + Nominatim) and Russian Wikipedia. The MCP defines no credentials. **How is this different from the culture MCP?** The culture MCP covers museums, theatres and libraries in depth. This one is the broader list of things worth seeing — attractions, viewpoints, fountains and street art — plus a distance-sorted walking shortlist. **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 sights near a point?** 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.