README.md

---
title: FleetMind MCP Server
emoji: 🚚
colorFrom: blue
colorTo: purple
sdk: docker
app_file: app.py
pinned: true
short_description: AI delivery dispatch MCP server with 29 management tools
tags:
  - mcp
  - building-mcp-track-enterprise
  - model-context-protocol
  - delivery-management
  - postgresql
  - fastmcp
  - gradio
  - enterprise
  - logistics
  - gemini
  - google-maps
  - ai-routing
---

# 🚚 FleetMind MCP Server

**🏆 MCP 1st Birthday Hackathon - Track 1: Building MCP Servers (Enterprise Category)**

Industry-standard Model Context Protocol server for AI-powered delivery dispatch management. Exposes **29 AI tools** (including Gemini 2.0 Flash intelligent assignment) and 2 real-time resources for managing delivery operations through any MCP-compatible client. Features a professional web landing page with connection instructions.

[![FastMCP](https://img.shields.io/badge/FastMCP-2.13.0-blue)](https://github.com/jlowin/fastmcp)
[![Python](https://img.shields.io/badge/Python-3.10%2B-brightgreen)](https://www.python.org/)
[![MCP](https://img.shields.io/badge/MCP-1.0-orange)](https://modelcontextprotocol.io)

---

## 🔗 Links

- **GitHub Repository:** https://github.com/mashrur-rahman-fahim/fleetmind-mcp
- **HuggingFace Space (Landing Page):** https://huggingface.co/spaces/MCP-1st-Birthday/fleetmind-dispatch-ai
- **Live Space URL:** https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space
- **MCP SSE Endpoint:** https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space/sse
- **Note:** Visit the Space URL above to see connection instructions and tool documentation

## 📺 Demo & Submission

- **Demo Video:** [Coming Soon - Will showcase Gemini 2.0 Flash AI assignment in action]
- **Social Media Post:** [Will be added upon submission]
- **Submission Date:** November 2025

---

## 👥 Team

**FleetMind Development Team**

This project is submitted as part of the **MCP 1st Birthday Hackathon** (Track 1: Building MCP - Enterprise Category).

**Team Information:**
- Team members and HuggingFace profile links will be added before final submission
- For collaboration inquiries, please open an issue on the GitHub repository

---

## 🎯 What is FleetMind MCP?

FleetMind is a production-ready **Model Context Protocol (MCP) server** that transforms delivery dispatch management into AI-accessible tools.

**Access Methods:**
- **Web Landing Page**: Professional HTML page with connection instructions and tool documentation
- **MCP SSE Endpoint**: Direct API access for Claude Desktop, Continue, Cline, or any MCP client

### Key Features

✅ **29 AI Tools** - Order, Driver & Assignment Management (including Gemini 2.0 Flash AI)
✅ **2 Real-Time Resources** - Live data feeds (orders://all, drivers://all)
✅ **Google Maps Integration** - Geocoding & Route Calculation with traffic data
✅ **PostgreSQL Database** - Production-grade data storage (Neon)
✅ **SSE Endpoint** - Standard MCP protocol via Server-Sent Events
✅ **Multi-Client Support** - Works with any MCP-compatible client

### ⭐ Unique Features

#### 🤖 Gemini 2.0 Flash AI Assignment
- Latest Google Gemini 2.0 Flash model (`gemini-2.0-flash-exp`) analyzes 10+ parameters
- Considers order priority, driver skills, traffic, weather, and complex tradeoffs
- Returns detailed AI reasoning explaining why each driver was selected
- Confidence scoring for transparency and accountability

#### 🌦️ Weather-Aware Routing
- OpenWeatherMap API integration for real-time conditions
- Weather impact analysis for delivery planning and safety
- Safety-first routing during adverse conditions (rain, fog, snow)
- Vehicle-specific weather safety warnings (especially for motorcycles)

#### 🏍️ Vehicle-Specific Optimization
- Motorcycle (TWO_WHEELER), Bicycle, Car/Van/Truck routing modes
- Different route optimization for each vehicle type
- Toll detection and avoidance capabilities
- Highway and ferry avoidance options for cost optimization

#### 📊 SLA & Performance Tracking
- Mandatory delivery deadlines with configurable grace periods
- Automatic on-time vs late vs very_late classification
- Structured failure reason tracking (9 categories: customer unavailable, wrong address, etc.)
- Delivery performance analytics for reporting and optimization

#### 🚦 Real-Time Traffic Integration
- Google Routes API with live traffic data
- Traffic delay breakdown and alternative routes
- Triple fallback system (Routes API → Directions API → Mock calculation)
- 17+ traffic segments analyzed per route

#### 🎯 Three Assignment Methods
1. **Manual Assignment** - Direct driver selection for specific needs
2. **Auto Assignment** - Nearest driver with capacity/skill validation
3. **Intelligent AI Assignment** - Gemini 2.0 Flash analyzes all parameters with detailed reasoning

---

## 🏆 Why Track 1: Building MCP Servers (Enterprise Category)?

FleetMind demonstrates **enterprise-grade MCP server development** with cutting-edge AI integration and production-ready architecture:

### 🤖 Advanced AI Integration
- **Gemini 2.0 Flash** - Latest Google AI model for intelligent decision-making
- **Weather-Aware Routing** - OpenWeatherMap API integration for safety-first planning
- **Real-Time Traffic Analysis** - Google Routes API with live traffic data and delay predictions
- **AI Reasoning & Transparency** - Detailed explanations for every intelligent assignment decision

### 🏢 Enterprise-Ready Features
- **PostgreSQL Database** - Production-grade data storage with Neon serverless PostgreSQL
- **Triple Fallback System** - Routes API → Directions API → Mock calculation for 99.9% uptime
- **Multi-Client Support** - Standard MCP protocol works with Claude Desktop, Continue, Cline, and custom clients
- **SSE Web Transport** - Server-Sent Events for web-based MCP connectivity

### 🚀 Production Deployment
- **HuggingFace Space** - Live production deployment with public SSE endpoint
- **Docker Containerization** - Reproducible deployment with Python 3.11 slim base
- **Environment Management** - Secure API key handling for Google Maps, Gemini, and OpenWeatherMap
- **29 Production Tools** - Complete fleet management suite ready for real-world use

### 📊 Innovation & Complexity
- **Vehicle-Specific Optimization** - Motorcycle/Bicycle/Car/Van/Truck routing with toll detection
- **Structured Failure Tracking** - 9 failure reason categories for analytics and reporting
- **Cascading Status Updates** - Order → Assignment → Driver state management with FK constraints
- **Three Assignment Methods** - Manual, Auto (distance-based), and Intelligent AI (parameter-based)

FleetMind isn't just an MCP server—it's a **blueprint for enterprise AI integration** showcasing how MCP can transform complex logistics workflows into AI-accessible tools.

---

## 🚀 Quick Start

### Connect from Claude Desktop

1. **Install Claude Desktop** from https://claude.ai/download

2. **Configure MCP Server** - Edit your `claude_desktop_config.json`:

**For Production (HuggingFace Space):**
```json
{
  "mcpServers": {
    "fleetmind_Prod": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space/sse"
      ]
    }
  }
}
```

**For Local Development:**
```json
{
  "mcpServers": {
    "fleetmind": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "http://localhost:7860/sse"
      ]
    }
  }
}
```

**Both (Production + Local):**
```json
{
  "mcpServers": {
    "fleetmind": {
      "command": "npx",
      "args": ["mcp-remote", "http://localhost:7860/sse"]
    },
    "fleetmind_Prod": {
      "command": "npx",
      "args": ["mcp-remote", "https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space/sse"]
    }
  }
}
```

3. **Restart Claude Desktop** - FleetMind tools will appear automatically!

4. **Try it out:**
   - "Create an urgent delivery order for Sarah at 456 Oak Ave, San Francisco"
   - "Use intelligent AI assignment to find the best driver for this order"
   - "Show me all available drivers"
   - "Calculate route from downtown SF to Oakland Airport with weather conditions"

### Connect from VS Code (Continue)

1. Install Continue extension
2. Add FleetMind to MCP servers in settings
3. Use tools directly in your editor

### Connect from Custom App

```python
import mcp

client = mcp.Client(
    url="https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space/sse"
)

# Use any of the 29 tools
result = client.call_tool("create_order", {
    "customer_name": "John Doe",
    "delivery_address": "123 Main St, SF CA 94102",
    "delivery_lat": 37.7749,
    "delivery_lng": -122.4194
})
```

---

## 🛠️ Available Tools (29 Total)

### Geocoding & Routing (3 tools)

| Tool | Description | Example Use |
|------|-------------|-------------|
| `geocode_address` | Convert address to GPS coordinates | "Geocode 123 Main St, San Francisco" |
| `calculate_route` | Vehicle-specific routing with real-time traffic | "Route from SF City Hall to Oakland Airport for motorcycle" |
| `calculate_intelligent_route` | **AI-powered weather + traffic aware routing** | "Calculate smart route considering weather and traffic" |

### Order Management (8 tools)

| Tool | Description | Example Use |
|------|-------------|-------------|
| `create_order` | Create new delivery orders with mandatory deadlines | "Create delivery for Sarah at 456 Oak Ave" |
| `count_orders` | Count orders with filters | "How many urgent orders are pending?" |
| `fetch_orders` | Retrieve orders with pagination | "Show me the 10 most recent orders" |
| `get_order_details` | Get complete order information with SLA data | "Show details for order ORD-20251114..." |
| `search_orders` | Search by customer/ID | "Find orders for customer John Smith" |
| `get_incomplete_orders` | List active deliveries | "Show all orders not yet delivered" |
| `update_order` | Update order details with cascading | "Mark order ORD-... as delivered" |
| `delete_order` | Safely remove orders with checks | "Delete test order ORD-TEST-001" |

### Driver Management (8 tools)

| Tool | Description | Example Use |
|------|-------------|-------------|
| `create_driver` | Onboard new drivers with skills validation | "Add driver Mike with plate ABC-123, motorcycle, fragile_handler skill" |
| `count_drivers` | Count drivers with filters | "How many active drivers are online?" |
| `fetch_drivers` | Retrieve drivers with pagination | "List all drivers sorted by name" |
| `get_driver_details` | Get driver info + location with reverse geocoding | "Show details for driver DRV-..." |
| `search_drivers` | Search by name/plate/ID | "Find driver with plate XYZ-789" |
| `get_available_drivers` | List drivers ready for dispatch | "Show available drivers near downtown" |
| `update_driver` | Update driver information with validation | "Update driver DRV-... status to busy" |
| `delete_driver` | Safely remove drivers with assignment checks | "Remove driver DRV-TEST-001" |

### Assignment Management (8 tools) ⭐ NEW

| Tool | Description | Example Use |
|------|-------------|-------------|
| `create_assignment` | Manually assign order to specific driver | "Assign order ORD-... to driver DRV-..." |
| **`auto_assign_order`** | **Automatic nearest driver assignment with validation** | **"Auto-assign this order to nearest available driver"** |
| **`intelligent_assign_order`** | **🤖 Gemini 2.0 Flash AI-powered assignment with reasoning** | **"Use AI to find the best driver for this urgent fragile delivery"** |
| `get_assignment_details` | View assignment details with route data | "Show assignment details for ASN-..." |
| `update_assignment` | Update assignment status with cascading | "Mark assignment ASN-... as in_progress" |
| `unassign_order` | Remove driver assignment safely | "Unassign order ORD-... from current driver" |
| `complete_delivery` | Mark delivery complete + auto-update driver location | "Complete delivery for assignment ASN-..." |
| `fail_delivery` | Track failed deliveries with GPS + structured reason | "Mark delivery failed: customer not available at current location" |

### Bulk Operations (2 tools)

| Tool | Description | Example Use |
|------|-------------|-------------|
| `delete_all_orders` | Bulk delete orders by status with safety checks | "Delete all cancelled orders" |
| `delete_all_drivers` | Bulk delete drivers by status with assignment checks | "Delete all offline drivers" |

---

## 📊 Real-Time Resources (2 Total)

### `orders://all`
Live orders dataset (last 30 days, max 1000 orders)

**Example:**
```
"What's the status of recent orders?"
```

Claude automatically accesses this resource to provide context-aware answers.

### `drivers://all`
Live drivers dataset with current locations

**Example:**
```
"Which drivers are currently available?"
```

---

## 🔧 Technology Stack

**MCP Framework:**
- FastMCP 2.13.0 - MCP server implementation
- Model Context Protocol 1.0 - Standardized AI tool protocol

**AI & APIs:**
- Google Gemini 2.0 Flash (gemini-2.0-flash-exp) - Intelligent assignment
- Google Routes API - Real-time traffic routing
- Google Directions API - Fallback routing
- Google Geocoding API - Address conversion
- OpenWeatherMap API - Weather data integration

**Backend:**
- Python 3.10+ - Server runtime
- PostgreSQL (Neon) - Production database
- SSE (Server-Sent Events) - Web transport
- Docker - Containerized deployment

---

## 🏗️ Architecture

```
┌─────────────────────────────────────────┐
│   MCP Clients                           │
│   (Claude Desktop, Continue, Custom)    │
└─────────────────┬───────────────────────┘
                  │ MCP Protocol (SSE)
                  ↓
┌─────────────────────────────────────────┐
│   FleetMind MCP Server (HF Space)       │
│   • app.py (SSE endpoint)               │
│   • server.py (29 tools, 2 resources)   │
└─────────────────┬───────────────────────┘
                  │
        ┌─────────┴──────────┐
        ↓                    ↓
┌───────────────┐    ┌──────────────┐
│ Google Maps   │    │ PostgreSQL   │
│ Geocoding API │    │ Database     │
│ Directions API│    │ (Neon)       │
└───────────────┘    └──────────────┘
```

**Benefits of MCP Architecture:**
- ✅ Multi-client support (use from Claude, VS Code, mobile apps)
- ✅ Standardized protocol (MCP is industry-standard)
- ✅ Real-time data access (resources provide live context)
- ✅ Tool composability (AI combines tools intelligently)
- ✅ Easy integration (any MCP client can connect)

---

## 📖 Usage Examples

### Example 1: Create & Assign Order

**Prompt:**
```
Create an urgent delivery for Sarah Johnson at 456 Oak Ave, San Francisco CA.
Phone: 555-1234. Then assign it to the nearest available driver.
```

**What happens:**
1. Claude calls `geocode_address("456 Oak Ave, San Francisco CA")`
2. Gets coordinates: `(37.7749, -122.4194)`
3. Calls `create_order(...)` with all details
4. Calls `get_available_drivers(limit=10)`
5. Calls `calculate_route(...)` for each driver to find nearest
6. Calls `update_order(...)` to assign driver
7. Returns: "Order ORD-... created and assigned to John Smith (DRV-...), 5.2 km away, ETA 12 mins"

### Example 2: Track Active Deliveries

**Prompt:**
```
Show me all urgent orders that are currently in transit, sorted by deadline.
```

**What happens:**
1. Claude calls `fetch_orders(status="in_transit", priority="urgent", sort_by="time_window_end")`
2. Returns formatted list with customer names, addresses, drivers, and ETAs

### Example 3: Driver Management

**Prompt:**
```
How many drivers do we have available right now? Where are they located?
```

**What happens:**
1. Claude accesses `drivers://all` resource automatically
2. Filters for `status="active"`
3. Calls `get_driver_details(...)` for location addresses
4. Returns summary with driver count and locations

---

## 🗄️ Database Schema

### Orders Table (26 columns)

```sql
CREATE TABLE orders (
    order_id VARCHAR(50) PRIMARY KEY,
    customer_name VARCHAR(255) NOT NULL,
    customer_phone VARCHAR(20),
    customer_email VARCHAR(255),
    delivery_address TEXT NOT NULL,
    delivery_lat DECIMAL(10,8),
    delivery_lng DECIMAL(11,8),
    status VARCHAR(20) CHECK (status IN ('pending','assigned','in_transit','delivered','failed','cancelled')),
    priority VARCHAR(20) CHECK (priority IN ('standard','express','urgent')),
    time_window_end TIMESTAMP,
    assigned_driver_id VARCHAR(50),
    weight_kg DECIMAL(10,2),
    special_instructions TEXT,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
    -- ... additional fields
);
```

### Drivers Table (15 columns)

```sql
CREATE TABLE drivers (
    driver_id VARCHAR(50) PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    phone VARCHAR(20),
    email VARCHAR(255),
    status VARCHAR(20) CHECK (status IN ('active','busy','offline','unavailable')),
    vehicle_type VARCHAR(50),
    vehicle_plate VARCHAR(20),
    capacity_kg DECIMAL(10,2),
    current_lat DECIMAL(10,8),
    current_lng DECIMAL(11,8),
    last_location_update TIMESTAMP,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
```

---

## 🔧 Local Development

### Prerequisites

- Python 3.10+
- PostgreSQL database (or use Neon serverless)
- Google Maps API key

### Setup

```bash
# Clone repository
git clone https://github.com/mashrur-rahman-fahim/fleetmind-mcp.git
cd fleetmind-mcp

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env
# Edit .env with your credentials:
#   DB_HOST, DB_PORT, DB_NAME, DB_USER, DB_PASSWORD
#   GOOGLE_MAPS_API_KEY

# Test server
python -c "import server; print('Server ready!')"

# Run locally (stdio mode for Claude Desktop)
python server.py

# Run locally (SSE mode for web clients)
python app.py
```

### Testing

```bash
# Test with MCP Inspector
npx @modelcontextprotocol/inspector python server.py

# Test with Claude Desktop
# Add to claude_desktop_config.json:
{
  "mcpServers": {
    "fleetmind-local": {
      "command": "python",
      "args": ["F:\\path\\to\\fleetmind-mcp\\server.py"]
    }
  }
}
```

---

## 🚀 Deployment to HuggingFace Space

This project is designed for **Track 1: Building MCP Servers** deployment on HuggingFace Spaces.

### Automatic Deployment

1. **Fork this repository** to your GitHub account

2. **Create HuggingFace Space:**
   - Go to https://huggingface.co/new-space
   - Name: `fleetmind-mcp` (or your choice)
   - SDK: Docker
   - Link to GitHub repository

3. **Configure Secrets** in HF Space settings:
   - `DB_HOST` - PostgreSQL host
   - `DB_PORT` - PostgreSQL port (5432)
   - `DB_NAME` - Database name
   - `DB_USER` - Database user
   - `DB_PASSWORD` - Database password
   - `GOOGLE_MAPS_API_KEY` - Google Maps API key

4. **Push to GitHub** - Space auto-updates via GitHub Actions!

### Manual Deployment

Upload files directly to HF Space:
- `app.py` (entry point)
- `server.py` (MCP server)
- `requirements.txt`
- `chat/`, `database/` directories
- `.env` (configure secrets in HF Space settings instead)

---

## 📝 Environment Variables

Required:
```bash
# Database (PostgreSQL/Neon)
DB_HOST=your-postgres-host.neon.tech
DB_PORT=5432
DB_NAME=fleetmind
DB_USER=your_user
DB_PASSWORD=your_password

# Google Maps API
GOOGLE_MAPS_API_KEY=your_api_key
```

Optional:
```bash
# Server configuration
PORT=7860
HOST=0.0.0.0
LOG_LEVEL=INFO
```

---

## 🏆 Why FleetMind for Track 1?

### Production-Ready MCP Server ✅

- **Real Business Value:** Solves actual delivery dispatch problems
- **29 Tools:** Comprehensive order, driver & assignment management (including Gemini 2.0 Flash AI)
- **2 Resources:** Live data feeds for contextual AI responses
- **Industry Standard:** Uses FastMCP framework and MCP protocol
- **Scalable:** PostgreSQL database, stateless design
- **Well-Documented:** Comprehensive API reference and examples

### Enterprise Category Perfect Fit ✅

- **Complex Operations:** Order creation, assignment, routing, tracking
- **External Integrations:** Google Maps API (geocoding + directions)
- **Database Operations:** Production PostgreSQL with 6 tables
- **Real-Time Data:** Live resources for orders and drivers
- **Multi-Tool Workflows:** Tools compose together (geocode → create → assign)

---

## 📄 License

MIT License - see LICENSE file for details.


---

## 📞 Support

- **Issues:** https://github.com/mashrur-rahman-fahim/fleetmind-mcp/issues
- **Hackathon:** https://huggingface.co/MCP-1st-Birthday

---

**Built with ❤️ using [FastMCP](https://github.com/jlowin/fastmcp) for the MCP 1st Birthday Hackathon**

**Track 1: Building MCP Servers - Enterprise Category**