🏭 FactoryMind AI

An AI-powered Smart Manufacturing Assistant built with NitroStack and the Model Context Protocol (MCP).

FactoryMind AI enables engineers, plant managers, and maintenance teams to interact with factory systems using natural language. It connects AI with manufacturing data to provide real-time insights, automate maintenance workflows, and improve operational efficiency in Industry 4.0 environments.

✨ Features

• 🤖 AI-powered manufacturing assistant

• 🔧 Machine health analysis

• 📈 Executive KPI dashboard

• ⚠️ Predictive maintenance recommendations

• 📦 Spare part availability checking

• 👨‍🔧 Automatic technician assignment

• 🎫 Maintenance ticket creation

• 🏭 Factory production monitoring

• 💬 Natural language interaction with factory systems using MCP

Related MCP server: foundry net-industrial

🛠 Tech Stack

• NitroStack

• Model Context Protocol (MCP)

• TypeScript

• Node.js

• OpenAI

• REST APIs

📁 Project Structure

FactoryMind-AI/
│
├── src/
│   ├── prompts/
│   ├── tools/
│   ├── services/
│   ├── workflows/
│   └── index.ts
│
├── .env.example
├── package.json
├── README.md
└── LICENSE

🚀 Getting Started

1. Clone the Repository

git clone https://github.com/<your-username>/FactoryMind-AI.git

cd FactoryMind-AI

2. Install Dependencies

npm install

3. Configure Environment Variables

Create a .env file from .env.example.

Example:

OPENAI_API_KEY=your_api_key
FACTORY_API_URL=http://localhost:3000
FACTORY_API_TOKEN=your_token

▶️ Run the Project

Development

npm run dev

Production

npm run build
npm start

MCP Setup

FactoryMind AI is built on the Model Context Protocol (MCP) using NitroStack.

Configure your MCP server and register the available tools before starting the application.

Example MCP configuration:

{
  "mcpServers": {
    "factorymind": {
      "command": "npm",
      "args": ["run", "start"]
    }
  }
}

Once connected, the assistant can invoke manufacturing tools through MCP.

Example Prompts

Analyze machine M-102.

Show the factory dashboard.

Show executive KPI dashboard.

Check spare part availability for machine M-102.

Assign the appropriate technician for machine M-102.

Create a maintenance ticket for machine M-102.

Analyze machine M-102, check spare part availability,
assign a technician, and create a maintenance ticket.

Example Workflow

User
   │
   ▼
FactoryMind AI
   │
   ▼
NitroStack
   │
   ▼
Model Context Protocol (MCP)
   │
   ├── Machine Health Tool
   ├── Production Dashboard Tool
   ├── Spare Parts Tool
   ├── Technician Assignment Tool
   └── Maintenance Ticket Tool
   │
   ▼
Factory Systems / APIs

🔒 Security

• Never commit API keys or secrets.

• Use environment variables.

• Keep sensitive configuration inside .env.

• The repository includes .env.example for reference.

📄 License

This project is licensed under the MIT License.

🤝 Contributing

Contributions are welcome!

1. Fork the repository

2. Create a feature branch

git checkout -b feature/new-feature

3. Commit your changes

git commit -m "Add new feature"

4. Push to GitHub

git push origin feature/new-feature

5. Open a Pull Request

👨‍💻 Author

Advaith K S

Built for smart manufacturing using NitroStack and the Model Context Protocol (MCP) to simplify factory operations through AI.