MRP Calculation

MRP (materials requirement planning) MCP which can extract data necessary for making an MRP calculation and make the calculation while showing the steps.

javascript

0

GitHub Stars

javascript

Language

7 months ago

First Indexed

3 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "brandon-butterwick-mrp_calculation": {
      "command": "node",
      "args": [
        "/path/to/mrp-calculator/dist/index.js"
      ]
    }
  }
}

This MCP server provides Material Requirements Planning (MRP) calculations to help you optimize procurement and scheduling. It exposes core MRP capabilities via the MCP protocol, allowing you to query delivery schedules, determine order needs, and perform period-based MRP calculations from your client or automation workflows.

How to use

You connect to the MRP MCP server from your MCP client to perform essential planning actions. Use the available tools to calculate when to place orders, how much to order, and how your delivery schedules map to your planning horizons. This enables you to align inventory levels with forecasted demand, reduce stockouts, and optimize procurement timing.

How to install

Prerequisites: you need Node.js and npm installed on your system.

# Install dependencies for the MRP server project
npm install

# Build the server
npm run build

# Run the server
node dist/index.js

Configuration

{
  "mcpServers": {
    "mrp": {
      "command": "node",
      "args": ["/path/to/mrp-calculator/dist/index.js"],
      "env": {}
    }
  }
}

Development notes

The server is implemented in TypeScript and uses the MCP SDK for the server architecture. It includes test cases to validate the MRP calculations and input validation logic.

Available tools

calculate_order_need

Calculates when and how much to order based on current inventory, forecast periods, delivery schedules, and order constraints.