Articles & News
Deep dives on open geospatial data, API design, and building map-powered applications.
Check Your Business Listing on OpenStreetMap (Free SEO Tool)
Score how complete and current your business is on OpenStreetMap. Free listing checker for local SEO, mappers, and area audits of stale cafes and shops.
How to Get Every EV Charging Station from OpenStreetMap (as GeoJSON)
Step-by-step guide to pulling EV charging stations from OpenStreetMap for any city or country as GeoJSON: tags, sockets, curl and Python, data quality caveats.
Free Maps for Developers: Draw Pins with OpenFreeMap, Compute with MapLark
Draw pins on a free map with OpenFreeMap and MapLibre, then get the data behind them from an OpenStreetMap API. Five real questions: building footprints, flood zones, rooftop solar, shadow studies and cafes.
Geospatial MCP Server: Give AI Agents Live OpenStreetMap Data
Ask an agent for the nearest pharmacy and it invents a street. Give it live OpenStreetMap and it looks the place up, checks hours, and walks the real network. How the MapLark MCP server does that.
Places API: Nearby Cafes, Restaurants, Pharmacies, and Opening Hours
Search nearby cafes, restaurants, pharmacies, ATMs, EV chargers, schools, and hospitals on OSM tags. Opening hours, nearest-first rank, and a live playground.
How to get building heights and calculate shadows from OpenStreetMap
Get building footprints from OpenStreetMap by querying closed ways tagged building. Read height from the height tag, or estimate it from building:levels when it is missing. Then compute shadows. Vector tiles clip footprints and drop height tags, so they are the wrong input.
OSM Vector Tiles vs Features API (Overpass Alternative)
Vector tiles draw an OpenStreetMap basemap; a features API (like Overpass, or the MapLark OSM Features API) queries it. Compare tags, geometry, filtering and output formats, and learn which one your app needs.
Building the New OSM Features API: A Planet-Scale Overpass Alternative
How we built a production OSM Features API on PostGIS: scaling the import to the full planet, the 1.5 TB storage footprint, the indexes that make popular-tag queries fast, and real measured performance against public Overpass.