FleetMind – Agentic AI Fleet Dispatch (MCP)

Case study, stack, and technical highlights

FleetMind – Agentic AI Fleet Dispatch (MCP)

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FleetMind – Agentic AI Fleet Dispatch (MCP) - Image 1

Project Details

Completed
Web Application

Enterprise Model Context Protocol server exposing 29 AI-accessible tools and 2 real-time resources, letting an LLM run end-to-end delivery dispatch (orders, drivers, assignments) through natural conversation. Autonomous agentic loop on Gemini 2.0 Flash plans and executes multi-step workflows; an AI assignment engine analyzes 10+ live signals (weather, traffic, vehicle fit) with transparent reasoning. 3-layer multi-tenant auth (SSE proxy, validation middleware, DB-level filtering) with SHA-256 hashed keys; deployed on HuggingFace Spaces via Docker.

Key Features

  • 29 MCP tools + 2 real-time resources
  • Autonomous multi-step agentic loop
  • AI assignment engine with 10+ live signals
  • 3-layer multi-tenant auth

Achievements

  • 3rd place — MCP 1st Birthday Hackathon (Anthropic & Gradio), 6100+ participants

Project Info

Status:Completed
Type:Web Application
Category:AI & Machine Learning
Created:7/15/2026

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Mashrur Rahman

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