# OpenRouteService MCP > OpenRouteService calculates complex routes and analyzes spatial data using OpenStreetMap data. It handles everything from basic directions for cars or bikes to solving multi-vehicle delivery problems, generating accurate reachability maps (isochrones), and finding the exact distance between multiple points. ## Overview - **Category:** developer-tools - **Price:** Free - **Tags:** routing, geocoding, isochrones, distance-matrix, vehicle-routing-problem, spatial-analysis ## Description Need to map out a logistical challenge? This MCP lets your AI client calculate optimal routes across any network type—car, bicycle, or walking path. You can generate detailed isochrone polygons showing exactly what areas are accessible within a set time limit, which is vital for urban planning. Beyond simple directions, you can compute distance matrices that map travel times between every combination of origins and destinations in your dataset. If you run delivery services, the VROOM solver handles complex vehicle routing problems with capacity constraints. Plus, if you only have raw GPS coordinates, the system cleans up noisy data points by snapping them to the nearest road segment. Connecting OpenRouteService through Vinkius gives your agent a single source for all these geospatial calculations. ## Tools ### calculate_directions Finds precise, active routes spanning a road network between specified points. ### get_elevation_line Provides altitude data for a sequence of coordinates along a calculated line path. ### search_country_boundary Filters search results to ensure locations stay within specific national or regional borders. ### reverse_geocode Converts a set of coordinates back into a readable, structured address description. ### geocode_search Identifies specific locations or routes within the OpenRouteService system boundaries. ### calculate_isochrones Generates polygons that show all areas reachable from a central point within a defined time or distance. ### calculate_matrix Computes detailed tables showing the travel duration and distance between multiple pairs of locations (M x N). ### check_optimization_status Retrieves the current status or results of a previously initiated optimization job. ### solve_vrp_optimization Runs an automated solver to determine the optimal sequence and assignment for multiple vehicles on a set list of jobs. ### snap_gps_to_road Corrects noisy GPS data by forcing coordinates onto the nearest segment of a known road network. ## Prompt Examples **Prompt:** ``` Calculate a driving route from Berlin to Munich with estimated time. ``` **Response:** ``` Route calculated (driving-car): Berlin → Munich. Distance: 585 km. Duration: 5h 42min. Route passes through Leipzig and Nuremberg. 2 toll sections detected. Want me to generate an isochrone from the destination or calculate the return route? ``` **Prompt:** ``` Show me all areas reachable within 15 minutes by car from Times Square. ``` **Response:** ``` Isochrone generated for Times Square (40.7580, -73.9855) with 15-minute driving range. The polygon covers approximately 12 km² including Midtown, Upper East/West Side, Chelsea, and parts of the East Village. GeoJSON available. Want me to also generate 5 and 10-minute isochrones for comparison? ``` **Prompt:** ``` Calculate the distance matrix between our 3 warehouses and 5 customer locations. ``` **Response:** ``` 3×5 distance matrix computed (driving-car). Shortest pair: Warehouse B → Customer 3 (8.2 km, 14 min). Longest pair: Warehouse A → Customer 5 (47.1 km, 52 min). Average delivery time across all pairs: 28 min. Want me to run VRP optimization to assign optimal warehouse-customer pairs? ``` ## Capabilities ### Plan multi-stop routes Calculates optimal paths between multiple waypoints, providing distance and estimated time for different modes of travel. ### Map service coverage areas Generates reachability polygons (isochrones) showing all points accessible within a specific driving or walking radius from a start point. ### Measure all-to-all distances Creates matrices that compute the distance and duration between every origin and destination in a list of locations. ### Solve complex delivery logistics Optimizes multi-vehicle routes, solving problems with limits on vehicle capacity or time windows. ### Standardize addresses and coordinates Converts street addresses into precise coordinates, or vice versa, using reliable boundary filtering. ## Use Cases ### Optimizing a multi-warehouse delivery network A logistics manager needs the shortest total travel time for 12 deliveries using three different trucks. They ask their agent to run `solve_vrp_optimization`, which returns the optimal sequence and assignment, saving hours of manual spreadsheet work. ### Assessing urban accessibility for a new development An urban planner needs to know how many people can reach the site from major transit hubs within 10 minutes. They run `calculate_isochrones` centered on the hub, generating a precise polygon map instead of vague estimates. ### Calculating total mileage for consulting sites A field service lead has a list of 20 client addresses across three states. They use `calculate_matrix` to immediately get the distance and time between every single pair, allowing them to choose the most efficient cluster. ### Cleaning up faulty GPS tracking data A construction project generates noisy coordinates due to signal interference. The agent uses `snap_gps_to_road` on the raw feed, cleaning the points and making them usable for accurate distance calculations. ## Benefits - Stop guessing travel time. Use `calculate_matrix` to get accurate duration and distance measurements between every pair of locations, making your estimates reliable. - Visualize service areas instead of just listing points. Generating isochrones with `calculate_isochrones` shows planners exactly what neighborhoods are within a 15-minute walk or drive. - Handle real-world logistics complexity. The VRP solver (`solve_vrp_optimization`) takes capacity and time limits into account, solving multi-stop delivery routes that simple mapping tools miss. - Clean up bad data instantly. If you collect messy GPS traces from a field team, `snap_gps_to_road` cleans the noise by snapping coordinates directly onto usable road segments. - Convert points to addresses and vice versa. Use `reverse_geocode` to take a random coordinate point and immediately get a human-readable street address for reporting. ## How It Works The bottom line is that your agent handles all the complex geographical calculations; you just ask it what problem needs solving. 1. You ask your AI client to solve a spatial problem—for example, calculating routes for five different locations. 2. The MCP invokes the necessary calculation (like distance matrix or VRP optimization) using OpenStreetMap data in the background. 3. Your agent receives structured JSON output containing calculated distances, optimal paths, and detailed coordinates. ## Frequently Asked Questions **How do I use OpenRouteService to find the best route for multiple stops?** You can calculate optimal routes using `solve_vrp_optimization`. This tool solves complex vehicle routing problems, assigning the most efficient sequence of jobs while respecting capacity and time limits. **Is OpenRouteService better than general mapping APIs for distance calculations?** Yes. While other services provide basic directions, this MCP offers `calculate_matrix` which computes detailed duration and distance between every single pair of points in a list, giving you comprehensive coverage. **What if my GPS data is messy or noisy?** Use the `snap_gps_to_road` tool. It cleans up coordinates by snapping them to the nearest actual road segment, making your raw field data usable for accurate routing. **Can I find out what address corresponds to a set of latitude/longitude points?** You use `reverse_geocode`. This tool takes coordinates and performs structural extraction, returning the corresponding readable street address details from OpenStreetMap boundaries. **How do I check if an area is reachable within a certain time limit using OpenRouteService?** Run `calculate_isochrones`. This generates a precise polygon showing every point accessible from your starting location within the specified time or distance, perfect for service zone analysis.