MCP System Info Server
A lightweight MCP server that provides real-time hardware statistics including CPU, memory, disk, and NVIDIA GPU usage. It enables users to monitor system performance and retrieve comprehensive host machine specifications through a standardized interface.
README
MCP System Info Server
A lightweight MCP (Model Context Protocol) server that provides real-time system information including CPU, memory, disk, and GPU statistics.
Features
| Category | Information Provided |
|---|---|
| System | System name, node name, OS release/version, machine type, processor |
| CPU | Processor name, physical/logical cores, frequency, usage percentage |
| Memory | Total, available, used memory (GB), utilization percentage |
| Disk | Total, used, free space (GB), utilization percentage |
| GPU | Name, memory (total/used/free), utilization, temperature (NVIDIA only) |
Prerequisites
- Python 3.10+
- uv - Fast Python package manager
Installation
# Clone or navigate to the project directory
cd mcp
# Install dependencies (handled automatically by uv)
uv sync
Screenshots


Usage
Running Standalone
uv run sysinfo.py
Testing with MCP Inspector
uv run mcp dev sysinfo.py
Claude Desktop Configuration
Add this to your Claude Desktop configuration file:
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"sysinfo": {
"command": "uv",
"args": [
"--directory",
"PATH OF THE FOLDER",
"run",
"sysinfo.py"
]
}
}
}
Available Tools
get_sysinfo
Returns comprehensive system information as a JSON object:
{
"system": {
"system_name": "Windows",
"node_name": "DESKTOP-XXX",
"os_release": "10",
"os_version": "10.0.19045",
"machine_type": "AMD64",
"processor": "Intel64 Family 6..."
},
"cpu": {
"processor_name": "Intel Core i7-10700K",
"physical_cores": 8,
"logical_cores": 16,
"cpu_frequency_mhz": 3800.0,
"cpu_usage_percent": 12.5
},
"memory": {
"total_gb": 32.0,
"available_gb": 18.5,
"used_gb": 13.5,
"utilization_percent": 42.2
},
"disk": {
"total_gb": 500.0,
"used_gb": 280.0,
"free_gb": 220.0,
"utilization_percent": 56.0
},
"gpu": [
{
"id": 0,
"name": "NVIDIA GeForce RTX 3080",
"memory_total_mb": 10240.0,
"memory_used_mb": 2048.0,
"memory_free_mb": 8192.0,
"gpu_utilization_percent": 15.0,
"temperature_c": 45
}
]
}
Dependencies
- mcp[cli] - MCP SDK with CLI support
- psutil - Cross-platform system information
- GPUtil - NVIDIA GPU information
- py-cpuinfo - Detailed CPU information
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
E2B
Using MCP to run code via e2b.