System Diagnostics MCP Server

This is a Python-based Model Context Protocol (MCP) server. It provides diagnostic capabilities:

1. get_system_metrics: Retrieves real-time CPU, Memory, and Disk usage metrics.

2. list_top_processes: Lists top running processes sorted by CPU or Memory usage.

3. check_port_status: Verifies if a specific TCP port is open on a given host.

Prerequisites

• Python 3.10+

• uv (for ultra-fast dependency management)

• Docker (optional, for containerized execution)

Local Setup (Using uv)

1. Clone the repository and navigate into the folder:

   git clone https://github.com/niketanjain/mcp-server-setup.git
   cd mcp-server-setup

2. Initialize the virtual environment and install dependencies:

   uv sync
   # OR if no lockfile:
   uv pip install mcp psutil pydantic starlette uvicorn

3. Run the server locally:

   uv run python server.py

   The server will start an HTTP/SSE server on http://localhost:6500/sse.

Running with Docker

1. Build the Docker image:

   docker build -t mcp-sysdiag-server .

2. Run the Docker container, exposing port 6500:

   docker run -p 6500:6500 mcp-sysdiag-server

Extending to Production

Check out production-grade.md for recommendations and best practices when extending this MCP server to a production environment.