Which integrations are available for this server?

Provides geocoding and routing capabilities using [Google](/mcp/servers/integrations/google) Maps API for address-to-GPS conversion and vehicle-specific routing with live traffic data, toll information, and fuel estimates. Stores and manages delivery orders, driver information, and assignment data with multi-tenant isolation using Neon serverless [PostgreSQL](/mcp/servers/integrations/postgresql) database.

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

AI-Powered Delivery Dispatch for the Modern Enterprise

The Problem: Delivery dispatch is complex—coordinating drivers, optimizing routes, handling weather delays, and meeting SLAs requires constant human oversight.

The Solution: FleetMind exposes 29 AI-accessible tools that let Claude (or any MCP client) manage your entire delivery operation through natural conversation.

The Impact: Dispatch managers can now say "Assign this urgent fragile delivery to the best available driver considering weather and traffic" and watch AI handle the complexity.

📺 See It In Action

Watch Gemini 2.0 Flash AI analyze weather, traffic, and driver capabilities to make intelligent assignment decisions with full reasoning transparency.

⚡ Quick Start (2 Minutes)

Step 1: Get Your API Key

👉 Generate API Key (copy immediately—shown once!)

Step 2: Configure Claude Desktop

Add to your claude_desktop_config.json:

{ "mcpServers": { "fleetmind": { "command": "npx", "args": [ "mcp-remote", "https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space/sse?api_key=YOUR_KEY_HERE" ] } } }

Step 3: Start Dispatching!

You: "Create an urgent delivery for Sarah at 456 Oak Ave, San Francisco, then use AI to find the best driver considering the current rain" Claude: Uses geocode_address → create_order → intelligent_assign_order Returns: "Order ORD-... assigned to Mike (DRV-...). AI selected Mike because: closest driver with cold-storage van, safest route in current weather, 15 min ETA."

🏆 Why FleetMind?

Feature	What It Does	Why It Matters
🤖 Gemini 2.0 Flash AI	Analyzes 10+ parameters for intelligent driver assignment	Better decisions than rule-based systems
🌦️ Weather-Aware Routing	OpenWeatherMap integration for safety-first planning	Reduces weather-related delivery failures
🔐 Multi-Tenant Auth	Complete data isolation via deterministic user_id	Enterprise-ready security out of the box
📊 SLA Tracking	Automatic on-time/late/very-late classification	Built-in performance analytics
🚦 Real-Time Traffic	Google Routes API with live traffic data	Accurate ETAs, not guesstimates
🏍️ Vehicle Optimization	Motorcycle, bicycle, car, van, truck routing	Right routes for each vehicle type

🛠️ The 29 Tools

Tool	Description
`geocode_address`	Convert address → GPS coordinates
`calculate_route`	Vehicle-specific routing with traffic, tolls, fuel estimates
`calculate_intelligent_route`	AI-powered routing with weather + traffic analysis

Tool	Description
`create_order`	Create delivery with mandatory deadline & SLA tracking
`count_orders`	Count by status/priority with breakdowns
`fetch_orders`	Paginated list with filters
`get_order_details`	Full order info including timing data
`search_orders`	Find by customer name/email/phone/ID
`get_incomplete_orders`	Active deliveries shortcut
`update_order`	Modify order with cascading updates
`delete_order`	Safe deletion with assignment checks

Tool	Description
`create_driver`	Onboard with vehicle type, skills, capacity
`count_drivers`	Count by status/vehicle with breakdowns
`fetch_drivers`	Paginated list with filters
`get_driver_details`	Full info with reverse-geocoded location
`search_drivers`	Find by name/plate/phone/ID
`get_available_drivers`	Ready-for-dispatch shortcut
`update_driver`	Modify with location auto-timestamp
`delete_driver`	Safe deletion with assignment checks

Tool	Description
`create_assignment`	Manual driver selection
`auto_assign_order`	Nearest driver + capacity/skill validation
`intelligent_assign_order`	🤖 Gemini 2.0 Flash AI with full reasoning
`get_assignment_details`	Query by assignment/order/driver ID
`update_assignment`	Status transitions with cascading
`unassign_order`	Revert to pending safely
`complete_delivery`	Mark done + auto-update driver location
`fail_delivery`	Track failure with GPS + structured reason

Tool	Description
`delete_all_orders`	Mass delete with status filter & safety checks
`delete_all_drivers`	Mass delete with assignment safety blocks

🏗️ Architecture

┌──────────────────────────────────────────────────────────────┐ │ MCP Clients │ │ Claude Desktop • Continue • Cline • Custom Apps │ └─────────────────────────────┬────────────────────────────────┘ │ SSE: /sse?api_key=fm_xxx ▼ ┌──────────────────────────────────────────────────────────────┐ │ Authentication Proxy (proxy.py) │ │ • Captures API key from SSE connection │ │ • Links session_id → api_key for tool calls │ │ • Keep-alive pings every 30s │ └─────────────────────────────┬────────────────────────────────┘ ▼ ┌──────────────────────────────────────────────────────────────┐ │ FastMCP Server (server.py) │ │ • ApiKeyAuthMiddleware validates every call │ │ • 29 tools with user_id filtering │ │ • 2 real-time resources (orders://all, drivers://all) │ └──────────┬──────────┬────────────┬──────────┬────────────────┘ ▼ ▼ ▼ ▼ ┌──────────┐ ┌─────────┐ ┌──────────┐ ┌───────────┐ │PostgreSQL│ │ Google │ │ Gemini │ │OpenWeather│ │ (Neon) │ │Maps API │ │2.0 Flash │ │ Map API │ │ user_id │ │Geocoding│ │Intelligent││ Weather │ │isolation │ │ Routing │ │Assignment│ │ Data │ └──────────┘ └─────────┘ └──────────┘ └───────────┘

🔐 Authentication & Security

FleetMind uses a 3-layer authentication system for enterprise-grade security:

Layer	Component	Function
1	Proxy	Captures API key from URL, links sessions
2	Middleware	Validates every tool call, injects user context
3	Database	All queries filter by `user_id` (complete isolation)

Security Features:

✅ SHA-256 hashed key storage (never plaintext)
✅ One-time key display (can't retrieve later)
✅ Deterministic user_id from email (key rotation preserves data)
✅ Production safeguards (SKIP_AUTH blocked when ENV=production)

1. Generate API Key → user_id = user_{MD5(email)[:12]} 2. Configure Claude → URL includes ?api_key=fm_xxx 3. SSE Connection → Proxy captures and stores key 4. Tool Call → Proxy injects key, middleware validates 5. Database Query → WHERE user_id = 'user_xxx' 6. Result → Only user's own data returned

🚀 Deployment

Production (HuggingFace Space)

Already deployed at: https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space

Local Development

git clone <repository-url> cd fleetmind-mcp pip install -r requirements.txt # Configure .env with your API keys python start_with_proxy.py # Runs proxy (7860) + FastMCP (7861)

📊 Technical Specifications

Metric	Value
Tools	29
Resources	2 (orders://all, drivers://all)
Database	PostgreSQL (Neon serverless)
AI Model	Gemini 2.0 Flash (gemini-2.0-flash-exp)
Transport	SSE (Server-Sent Events)
Framework	FastMCP 2.13.0
Language	Python 3.10+

🔗 Links

Resource	URL
Live Demo	https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space
MCP Endpoint	https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space/sse
Generate API Key	https://mcp-1st-birthday-fleetmind-dispatch-ai.hf.space/generate-key
HuggingFace Space	https://huggingface.co/spaces/MCP-1st-Birthday/fleetmind-dispatch-ai

👥 Team

FleetMind Development Team

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

📄 License

MIT License - see LICENSE for details.

Built with ❤️ using

MCP FastMCP Python

FleetMind MCP Server