Provides tools for monitoring Docker containers, including status, uptime, ports, and image information.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@System Monitor MCP Server Show me the current CPU and memory usage"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Give your AI agent real-time access to system metrics, process management, and container orchestration.
{
"mcpServers": {
"system-monitor": {
"command": "python",
"args": ["-m", "server"],
"env": {
"PYTHONPATH": "${workspaceFolder}/src"
}
}
}
}{
"experimental": {
"mcpServers": {
"system-monitor": {
"command": "python",
"args": ["server.py"]
}
}
}
}docker build -t system-monitor-mcp .
docker run -v /var/run/docker.sock:/var/run/docker.sock system-monitor-mcpRelated MCP server: Systems Manager
Tool | Description | Returns |
| CPU, memory, swap usage | CPU%, Memory%, Swap%, Load avg |
| Running processes sorted by CPU/memory | PID, name, CPU%, memory%, status |
| Disk usage per mount point | Mount, total, used, available, usage% |
| Docker container status | Container name, status, uptime, ports, image |
| Tail log files | Last N lines with timestamps |
Self-monitoring — AI agents that monitor their own infrastructure
DevOps automation — Deploy, restart, and manage services autonomously
Incident response — Detect and diagnose issues in real-time
Resource optimization — Analyze usage patterns and suggest cost savings
Python 3.10+
Linux (most features) / macOS (partial) / Windows (limited)
Docker (optional — for container monitoring)
psutil, mcp, docker-py
Read-only by design — no kill/rm/create operations exposed
No root required — runs with user-level permissions
Sandboxed log access — path traversal protection built in
Part of the Hermes Agent ecosystem
This server cannot be deployed
Give your AI agents the tools to build, manage, and run automation workflows.
Provides capabilities that let LLM agents perform a range of infrastructure management tasks.
Operate Linux, macOS and Windows from your LLM. Every action runs through an auditable allowlist.
Connect, monitor, and control AI agents — tasks, approvals, schedules, and governance.
