Parallels RAS MCP Server (Python)

What is Parallels RAS MCP Server (Python)?

This MCP server provides a REST API backend to interact with Parallels Remote Application Server (RAS) for session management and app publishing. It is built with FastAPI and includes a client library for integration.

How to use Parallels RAS MCP Server (Python)?

Clone the repository, install dependencies via pip install -r requirements.txt, set RAS_API_URL, RAS_USERNAME, and RAS_PASSWORD in a .env file, then run the server using bash run.sh. Use the provided RASMCPClient in Python to call endpoints like get_sessions() and publish_application().

Key features of Parallels RAS MCP Server (Python)

• Lists current sessions via the RAS REST API
• Publishes remote applications
• FastAPI-based backend for easy scaling
• Simple client library for integration

Use cases of Parallels RAS MCP Server (Python)

• Monitor active user sessions on a Parallels RAS deployment
• Automate publishing of remote applications (e.g., Notepad)
• Build custom management tools on top of RAS session data

FAQ from Parallels RAS MCP Server (Python)

What are the prerequisites to run this server?

Python 3 and the dependencies in requirements.txt. You also need access to a Parallels RAS REST API endpoint.

How do I authenticate with the RAS API?

Set the RAS_USERNAME, RAS_PASSWORD, and RAS_API_URL environment variables in a .env file before starting the server.

How do I start the server?

After setting up the environment, run bash run.sh from the project root.

What does the client library do?

It provides a RASMCPClient class that connects to the MCP server at http://localhost:8000 and exposes methods like get_sessions() and publish_application().

Can I submit this server to the MCP registry?

Yes, the README directs you to submit at https://mcp.so/submit.