FactoryMind AI
Enables engineers and plant managers to interact with manufacturing systems using natural language, providing machine health analysis, KPI dashboards, predictive maintenance, and automated workflow execution via MCP.
README
š 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
- š¤ AI-powered manufacturing assistant
- š§ Machine health analysis
- š Executive KPI dashboard
- ā ļø Predictive maintenance recommendations
- š¦ Spare part availability checking
- šØāš§ Automatic technician assignment
- š« Maintenance ticket creation
- š Factory production monitoring
- š¬ Natural language interaction with factory systems using MCP
š Tech Stack
- NitroStack
- Model Context Protocol (MCP)
- TypeScript
- Node.js
- OpenAI
- REST APIs
š Project Structure
FactoryMind-AI/
ā
āāā src/
ā āāā prompts/
ā āāā tools/
ā āāā services/
ā āāā workflows/
ā āāā index.ts
ā
āāā .env.example
āāā package.json
āāā README.md
āāā LICENSE
š 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
ā¶ļø 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
ā
ā¼
FactoryMind AI
ā
ā¼
NitroStack
ā
ā¼
Model Context Protocol (MCP)
ā
āāā Machine Health Tool
āāā Production Dashboard Tool
āāā Spare Parts Tool
āāā Technician Assignment Tool
āāā Maintenance Ticket Tool
ā
ā¼
Factory Systems / APIs
š Security
- Never commit API keys or secrets.
- Use environment variables.
- Keep sensitive configuration inside
.env. - The repository includes
.env.examplefor reference.
š License
This project is licensed under the MIT License.
š¤ Contributing
Contributions are welcome!
- Fork the repository
- Create a feature branch
git checkout -b feature/new-feature
- Commit your changes
git commit -m "Add new feature"
- Push to GitHub
git push origin feature/new-feature
- Open a Pull Request
šØāš» Author
Advaith K S
Built for smart manufacturing using NitroStack and the Model Context Protocol (MCP) to simplify factory operations through AI.
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