CADCAMfun MCP Server

A Model Context Protocol (MCP) server for CAD/CAM applications that provides AI-powered design assistance, toolpath optimization, and machining parameter recommendations.

Overview

This MCP server exposes resources, tools, and prompts for CAD/CAM operations, allowing LLM applications to:

- Generate CAD components from text descriptions
- Optimize G-code for CNC machines
- Analyze CAD designs for manufacturability, structural integrity, and cost
- Get optimal cutting parameters for specific materials and tools
- Save components and toolpaths to the database
- Access CAD/CAM libraries, materials, and tools

Features

- Resources: Access component data, toolpaths, projects, materials, and machine configurations
- Tools: Generate CAD components, optimize G-code, analyze designs, calculate cutting parameters
- Prompts: Generate component designs, get machining parameters, and suggest design improvements
- Chat: Interactive assistance for CAD/CAM questions

Requirements

- Node.js 18+
- PostgreSQL database
- TypeScript 5.0+
- Prisma ORM

Installation

1. Clone the repository:
``bash
git clone https://github.com/yourusername/cadcamfun-mcp-server.git
cd cadcamfun-mcp-server
`

2. Install dependencies:
`bash
npm install
`

3. Configure environment variables:
`bash
cp .env.example .env
# Edit the .env file with your database credentials and settings
`

4. Apply database migrations:
`bash
npx prisma migrate dev
`

5. Build the project:
`bash
npm run build
`

Running the Server

$3

To run as an HTTP server (recommended for web applications):

`bash
npm run start:http
`

The server will start at http://localhost:3000/mcp by default.

$3

To run as a stdio server (useful for command-line tools):

`bash
npm run start:stdio
`

Docker Deployment

$3

- Docker and Docker Compose
- API key for Anthropic Claude

$3

1. Set up the environment variables:

Create a .env file in the root directory with your API key:
`
ANTHROPIC_API_KEY=your-api-key-here
`

2. Start the containers:
`bash
cd docker
docker-compose up -d
`

3. Initialize the database:
`bash
docker-compose exec mcp-server npm run setup-db
`

4. Access the server at http://localhost:3000/mcp

API Reference

$3

| URI | Description |
|-----|-------------|
| version://app | Application version information |
| component://{id} | Get component by ID |
| toolpath://{id} | Get toolpath by ID |
| project://{id} | Get project by ID |
| cam://materials | List available materials |
| cam://tools | List available cutting tools |
| cam://machine-configs | List available machine configurations |
| cad://library-items | List public library items |

$3

| Name | Description |
|------|-------------|
| generate-cad-component | Generate CAD components from text description |
| optimize-gcode | Optimize G-code for CNC machines |
| analyze-design | Analyze a CAD design for various aspects |
| get-cutting-parameters | Get optimal cutting parameters |
| save-component | Save a component to the database |
| save-toolpath | Save a toolpath to the database |

$3

| Name | Description |
|------|-------------|
| generate-cad-component | Generate CAD components from description |
| suggest-cad-improvements | Get suggestions for improving a CAD model |
| machining-parameters-advice | Get advice on machining parameters |

Client Usage Example

`typescript
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";

// Create client
const client = new Client({
name: "My CADCAMfun Client",
version: "1.0.0"
});

// Connect to server
const serverUrl = new URL("http://localhost:3000/mcp");
const transport = new StreamableHTTPClientTransport(serverUrl);
await client.connect(transport);

// Generate a CAD component
const result = await client.callTool({
name: "generate-cad-component",
arguments: {
description: "A simple 10mm x 10mm x 2mm base plate with 4 mounting holes",
complexity: "simple",
style: "precise"
}
});

console.log("Generated Component:", result.content[0].text);
`

Using with Claude and Cursor

To use the CADCAMfun MCP server with Claude and Cursor, you'll need to:

1. Start the MCP server
2. Configure Cursor to use the MCP server as a language model provider
3. Use Claude via the MCP server to assist with CAD/CAM tasks

This setup allows you to leverage Claude's capabilities through the MCP protocol, enhancing your CAD/CAM workflow with AI assistance.

Project Structure

`
cadcamfun-mcp-server/
├── .env # Environment variables
├── .env.example # Example environment file
├── .gitignore # Git ignore file
├── package.json # Node.js package configuration
├── tsconfig.json # TypeScript configuration
├── prisma/ # Prisma ORM files
│ └── schema.prisma # Database schema
├── src/ # Source code
│ ├── index.ts # Main entry point
│ ├── mcp-server.ts # MCP server implementation
│ ├── types/ # TypeScript type definitions
│ │ └── index.ts # Types used in the server
│ ├── services/ # Service implementations
│ │ ├── aiService.ts # AI service implementation
│ │ ├── cadService.ts # CAD service implementation
│ │ └── camService.ts # CAM service implementation
├── dist/ # Compiled JavaScript files
├── scripts/ # Utility scripts
│ └── setup-db.ts # Database setup script
└── docker/ # Docker deployment files
├── Dockerfile # Docker image definition
└── docker-compose.yml # Docker Compose configuration
`

Available Environment Variables

| Variable | Description | Default |
|----------|-------------|---------|
| DATABASE_URL | PostgreSQL connection string | postgresql://username:password@localhost:5432/cadcamfun |
| DIRECT_DATABASE_URL | Direct PostgreSQL connection | Same as DATABASE_URL |
| TRANSPORT | Transport type (http or stdio) | http |
| PORT | HTTP server port | 3000 |
| ANTHROPIC_API_KEY | API key for Anthropic Claude | |
| AI_MODEL | Default AI model | claude-3-7-sonnet-20250219 |
| AI_MAX_TOKENS | Maximum tokens for AI responses | 6000 |
| AI_TEMPERATURE | Temperature for AI generation | 0.7 |
| AI_CACHE_ENABLED | Enable AI response caching | true |
| AI_ANALYTICS_ENABLED | Enable AI analytics | true |
| MCP_ENABLED | Enable MCP protocol | true |
| MCP_STRATEGY | MCP caching strategy | balanced |
| MCP_CACHE_LIFETIME | Cache lifetime in milliseconds | 3600000 |
| CORS_ORIGINS | Allowed CORS origins | http://localhost:3000,https://cadcam.example.com |
| JWT_SECRET` | Secret for JWT tokens | |

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT