Skip to main content
Glama
ProTech001
by ProTech001

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

Related MCP server: ParaView-MCP

Prerequisites

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)

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}
}
F
license - not found
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
1Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ProTech001/mmar-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server