RouteKit MCP

Route optimization API for Brazil. First MCP server for route optimization.

Install

npx routekit-mcp

Or configure in your MCP client:

Claude Desktop / Claude Code

{
  "mcpServers": {
    "routekit": {
      "command": "npx",
      "args": ["-y", "routekit-mcp"],
      "env": {
        "ROUTEKIT_API_KEY": "YOUR_KEY"
      }
    }
  }
}

Direct HTTP (no install needed)

{
  "mcpServers": {
    "routekit": {
      "type": "url",
      "url": "https://routekit.nexterait.com.br/mcp",
      "headers": {
        "X-API-Key": "YOUR_KEY"
      }
    }
  }
}

Get API Key

Get a free key (50 calls/month) at routekit.nexterait.com.br/static/signup.html

Tools

• calculate_route -- Driving route between points with real road distances and ETAs. Supports waypoints, encoded polyline geometry, turn-by-turn steps, and up to 3 alternative routes.
• distance_matrix -- NxN distance/duration matrix between up to 5000 locations (transparently chunked for large sets, cached for repeated queries).
• snap_to_road -- Snap a raw GPS coordinate to the nearest road segment. Returns the snapped point, distance from the original, and road name.
• isochrone -- Area reachable from a point within N minutes by car. Returns a GeoJSON Polygon useful for coverage analysis, depot placement, and service area definition.
• geocode -- Convert a Brazilian address or place name to latitude/longitude. Restricted to Brazil, in-house geocoder with no third-party dependency. Built-in fuzzy fallback handles abbreviations ("Av" -> "Avenida"), accents, and token drops.
• geocode_batch -- Geocode up to 50 addresses in a single call with parallel execution. Perfect for delivery manifests or client lists.
• reverse_geocode -- Convert lat/lon to a human-readable Brazilian address with components (road, neighborhood, city, state, postcode).
• compare_routes -- Run optimize_routes under multiple balance strategies (minimize_vehicles, balance_tasks, minimize_distance) and return a side-by-side comparison with winners per metric.
• validate_eta -- Simulate a pre-defined route in Python and return the real arrival times plus any constraint violations. Use when you already have a fixed order of stops and just need the ETAs.
• optimize_routes -- Advanced VRP solver:
  • tasks (single-location jobs) and/or shipments (paired pickup+delivery, same vehicle)
  • Constraints: time windows (multiple per task), skills, multi-dimensional capacity, breaks, priorities
  • Per-vehicle costs (fixed, per_hour, per_km, per_task_hour), max_tasks, max_travel_time_min, max_distance_km
  • balance_mode: minimize_vehicles (default), balance_tasks, or minimize_distance
  • setup_min separate from service_min (setup charged once per location)
  • setup_per_type / service_per_type for different times per technician/vehicle type
  • vehicle.type tags for per-type time/cost modeling
  • end_lat / end_lon for open routes with different destination (e.g. driver ends at home)
  • Mixed-profile fleets (car / bike / foot) with per-vehicle profile
  • include_geometry=true returns encoded polylines per route (for maps)
  • matrix_overrides: user-provided per-pair travel time / distance overrides (for toll routes, restricted zones, known detours)
  • Up to 500 tasks / 250 shipments / 100 vehicles per request
  • Route-level and step-level violations reported when constraints are tight

Example

Ask your AI assistant:

"Geocode these addresses and optimize 10 deliveries in Sao Paulo for 2 drivers -- the senior finishes each stop in 20 min, the junior in 45 min. Balance tasks evenly, end both at the same warehouse, include the route polylines so I can draw them on a map."

The AI will call geocode, then optimize_routes with vehicle.type, `serv

... View full README on GitHub