AI Production Planner MCP (auto-planner-mcp)

An Industry 4.0 AI Production Planning MCP (Model Context Protocol) Server for automotive manufacturing lines. This system provides unified assembly queue management, intelligent build plan resequencing, Just-In-Sequence (JIS) inventory tracking, Overall Equipment Effectiveness (OEE) analytics, and financial downtime impact calculations.

📐 System Architecture & Structure

auto-planner-mcp/
├── data/                      # Industry 4.0 Mock Datasets
│   ├── assembly_queue.json    # Active vehicle assembly queue (VINs, models, seat types)
│   ├── inventory_jit.json     # Just-In-Time/Sequence parts inventory & ETA tracking
│   └── station_oee.json       # Assembly station efficiency & operational status
├── teammates/                 # Core Production Logic Engines
│   ├── dev_a/                 # Assembly Queue & Resequencing Module
│   │   ├── __init__.py
│   │   └── logic.py
│   └── dev_b/                 # Inventory & OEE Analytics Module
│       ├── __init__.py
│       └── logic.py
├── package.json               # NitroStack MCP server configuration
└── tsconfig.json              # TypeScript configuration

Related MCP server: NitroStack Calculator MCP Server

✨ Features & Production Tools

🚘 Assembly Queue & Resequencing Module

• get_assembly_sequence(shift_id: str, line_id: str)

  • Retrieves the active build queue for a specified shift and assembly line.

• resequence_build_plan(delay_reason: str, missing_option: str)

  • Dynamically resequences the assembly line schedule when part shortages occur (e.g., missing seat trims) by prioritizing available vehicle configurations and shifting delayed VINs to the end of the queue.

🏭 Inventory & Equipment Analytics Module

• check_jis_inventory(part_number: str, vin_sequence: str = None)

  • Checks stock levels, supplier ETAs, and shortage indicators for required JIS automotive components.

• calculate_station_oee(station_id: str)

  • Calculates Overall Equipment Effectiveness ($OEE = Availability \times Performance \times Quality$) for assembly stations (e.g., STATION_WELDING).

• estimate_downtime_cost(stopped_station_id: str)

  • Computes estimated financial losses based on station downtime duration (assumes $$22,000/\text{min}$ for non-running stations).

📊 Data Schemas

🚀 Running the MCP Server

# Start in development mode
npm run dev

# Build the project
npm run build

# Start production server
npm start