OpenRouteService MCP. Calculate complex routes with real-world constraints.

This server handles complex geospatial math—all backed by OpenStreetMap data. Forget straight-line estimates; this is for calculating routes and logistics flows that respect real-world road networks.

Preparing Your Data

Before you calculate anything, you gotta make sure your inputs are clean. You can turn human-readable addresses into precise geographic coordinates using geocode_search. When you know the coordinates already, use reverse_geocode to get back to a nearby street address or property boundary. If your data is messy—like from a handheld GPS unit—run snap_gps_to_road; it corrects noisy location points so they sit exactly on the nearest defined road segment.

For searches that need to stay contained, use search_country_boundary to filter results strictly within specific international lines.

Mapping Travel & Reachability

You can determine the shortest path between multiple waypoints for cars, bikes, or pedestrians using calculate_directions. This gives you an optimized route along with accurate distance and estimated travel time. If you need a full comparison chart showing how every point relates to every other point in your list, run calculate_matrix; it computes complete travel times and distances between all origins and destinations provided.

To figure out the area of coverage—like determining where you can get within 15 minutes driving from one spot—you generate an accessibility polygon map using calculate_isochrones. This function takes a single point and maps every location reachable within defined time or distance limits.

Advanced Logistics Solving

For real multi-stop logistics problems, you need the heavy artillery. You run advanced vehicle routing algorithms (VROOM) using solve_vrp_optimization. Just feed it your list of delivery jobs, vehicle capacities, and time windows; this tool spits out the absolute most efficient sequence of stops to keep total travel time down. If you're dealing with complex routes that involve vertical changes—say, calculating a hike or a mountain drive—you use get_elevation_line to get altitude data for every coordinate along your path.

When one of those big optimization jobs is running in the background, don't just wait; check its progress using check_optimization_status.

Putting It All Together

This system gives you a full lifecycle: You convert addresses to coordinates (geocode_search), clean up bad GPS points (snap_gps_to_road), and then determine the optimal multi-stop path (solve_vrp_optimization). Whether you're mapping service areas using calculate_isochrones or comparing travel times between dozens of potential sites with calculate_matrix, this server handles the complex geospatial math so you don't have to write a single line of routing logic.