flowchart LR
    A[AI Agent\nClaude / n8n / Custom] -->|MCP tool call| B[fleetsync-mcp\nMCP Server]
    B -->|REST API| C[FleetSync\nAPI v2]
    C -->|JSON response| B
    B -->|structured result| A

    subgraph Tools
        direction TB
        T1[Orders\nget · create · update · delete]
        T2[Routes\nget · create · update · delete]
        T3[Analytics\nanalyse route distances]
        T4[Drivers\nlist drivers]
    end

git clone https://github.com/RobsonAdvincula/fleetsync-mcp.git
cd fleetsync-mcp
npm install
npm run build

FLEETSYNC_API_KEY=your_api_key
FLEETSYNC_BASE_URL=https://api.fleetsync.io/v2

{
  "mcpServers": {
    "fleetsync": {
      "command": "node",
      "args": ["/path/to/fleetsync-mcp/dist/index.js"],
      "env": {
        "FLEETSYNC_API_KEY": "your_api_key"
      }
    }
  }
}

User: "How many deliveries do we have tomorrow and which routes are active?"

→ fleetsync_orders_by_date({ date: "2026-03-26" })
← { count: 47, orders: [...] }
→ fleetsync_routes_by_date({ date: "2026-03-26" })
← { count: 4, routes: [{ code: "R-01", driver: "...", orders: 12 }, ...] }

Agent: "47 orders across 4 active routes tomorrow. Route R-03 has the most stops (18)."

User: "Is route R-04 well optimised?"

→ fleetsync_analyze_route_distances({ code: "R-04", maxDistanceKm: 8 })
← {
    total_km: 34.2,
    avg_km: 2.1,
    violations_count: 2,
    violations: [
      { from: "ORD-112", to: "ORD-113", km: 11.4 },
      { from: "ORD-118", to: "ORD-119", km: 9.7 }
    ]
  }

Agent: "Route R-04 has 2 problematic segments exceeding 8km. Consider reordering stops 112→113 and 118→119."

distance = 2R × arcsin(√(sin²(Δlat/2) + cos(lat₁)cos(lat₂)sin²(Δlon/2)))