MMAR-MCP Server

An MCP (Model Context Protocol) server that connects Large Language Models to the MM-AR metamodeling platform, enabling users to create complete metamodels and model instances through natural language interaction.

Overview

MMAR-MCP exposes the MM-AR platform's capabilities through the Model Context Protocol:

• 62 tools for authentication, metamodel CRUD, and instance CRUD operations
• 5 resources providing platform architecture, VizRep templates, the meta²-model schema, attribute types, and a reference metamodel
• 3 prompts encoding guided workflows for metamodel creation, instance creation, and model analysis

Prerequisites

• Node.js v18 or later
• Docker (for running the MM-AR platform)
• An MCP-compatible host application (e.g., Cursor IDE, Claude Desktop, or any client supporting the Model Context Protocol)

Getting Started

Step 1: Set up the MM-AR Platform

The MCP server requires a running instance of the MM-AR platform. The easiest way to set it up is using Docker:

git clone https://github.com/MM-AR/mmar-docker-installation.git
cd mmar-docker-installation
docker compose up -d

This starts the full MM-AR stack: PostgreSQL database, API server (port 8000), Modeling Client (port 8080), and Metamodeling Client (port 8070). See the mmar-docker-installation README for detailed configuration options.

Step 2: Install the MCP Server

git clone https://github.com/ProTech001/mmar-mcp-server.git
cd mmar-mcp-server
npm install
npm run build

Step 3: Configure Your MCP Host

The server runs over STDIO and works with any MCP-compatible host. Below are configuration examples for common hosts.

Cursor IDE — add to .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "mmar": {
      "command": "node",
      "args": ["/absolute/path/to/mmar-mcp-server/dist/index.js"]
    }
  }
}

Claude Desktop — add to your Claude Desktop configuration file:

{
  "mcpServers": {
    "mmar": {
      "command": "node",
      "args": ["/absolute/path/to/mmar-mcp-server/dist/index.js"]
    }
  }
}

Replace /absolute/path/to/mmar-mcp-server with the actual path where you cloned the repository.

Step 4: Start Using

Once configured, you can use the guided prompts in your MCP host:

1. create-metamodel — Create a new modeling language from a natural language description
2. create-model — Create a model instance using an existing metamodel
3. analyze-model — Inspect and analyze existing models

For example: "Use the create-metamodel prompt to create a Petri Net modeling language with Place nodes, Transition nodes, and Arc connections."

Configuration

The server connects to the MM-AR API at http://localhost:8000 by default. If your MM-AR instance runs on a different host or port, set the MMAR_API_URL environment variable:

export MMAR_API_URL=http://your-mmar-host:8000

Project Structure

src/
├── index.ts              # Entry point
├── server.ts             # MCP server setup
├── config.ts             # Configuration
├── api-client.ts         # MM-AR REST API client
├── tools/
│   ├── index.ts          # Tool registration
│   ├── auth.tools.ts     # Authentication tools (3)
│   ├── meta.tools.ts     # Metamodel CRUD tools (26)
│   └── instance.tools.ts # Instance CRUD tools (33)
├── resources/
│   └── index.ts          # Resource definitions (5)
└── prompts/
    └── index.ts          # Prompt definitions (3)

Related Repositories

• mmar — Main MM-AR platform repository
• mmar-docker-installation — Docker-based setup for the full MM-AR platform
• mmar-server — MM-AR REST API server

License

ISC

Citation

If you use this software in your research, please cite:

@inproceedings{chima2026mmar-mcp,
  title={Agentic Creation of Modeling Languages: Extending the MM-AR Metamodeling Platform with MCP},
  author={Chima, Prosper and Fill, Hans-Georg and Curty, Simon},
  booktitle={Proceedings of the International Conference on Conceptual Modeling (ER), Demos and Posters},
  year={2026}
}