System Information MCP Server

System Information MCP Server

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Category
Visit Server

README

System Information MCP Server

A Model Context Protocol (MCP) server that provides real-time system information and metrics. This server exposes CPU usage, memory statistics, disk information, network status, and running processes through a standardized MCP interface.

Features

🛠️ Tools Available

  • get_cpu_info - Retrieve CPU usage, core counts, frequency, and load average
  • get_memory_info - Get virtual and swap memory statistics
  • get_disk_info - Disk usage information for all mounts or specific paths
  • get_network_info - Network interface information and I/O statistics
  • get_process_list - Running processes with sorting and filtering options
  • get_system_uptime - System boot time and uptime information
  • get_temperature_info - Temperature sensors and fan speeds (when available)

📚 Resources Available

  • system://overview - Comprehensive system overview with all metrics
  • system://processes - Current process list resource

⭐ Key Features

  • Real-time metrics with configurable caching
  • Cross-platform support (Windows, macOS, Linux)
  • Security-focused with sensitive data filtering
  • Performance optimized with intelligent caching
  • Comprehensive error handling
  • Environment variable configuration

Installation

Using uvx (Recommended)

The easiest way to install and use this MCP server is with uvx:

uvx install mcp-system-info

Then configure it in your MCP client (like Claude Desktop):

{
  "mcpServers": {
    "system-info": {
      "command": "uvx",
      "args": ["mcp-system-info"]
    }
  }
}

Development Installation

For local development:

  1. Clone the repository:

    git clone <repository-url>
    cd mcp-system-info
    
  2. Install dependencies:

    uv sync
    
  3. Run the server:

    uv run mcp-system-info
    

Development

Project Structure

mcp-system-info/
├── src/
│   └── system_info_mcp/
│       ├── __init__.py
│       ├── server.py          # Main FastMCP server
│       ├── tools.py           # Tool implementations
│       ├── resources.py       # Resource handlers
│       ├── config.py          # Configuration management
│       └── utils.py           # Utility functions
├── tests/                     # Comprehensive test suite
├── pyproject.toml            # Project configuration
└── README.md

Development Setup

  1. Install development dependencies:

    uv sync --dev
    
  2. Run tests:

    uv run pytest
    
  3. Run tests with coverage:

    uv run pytest --cov=system_info_mcp --cov-report=term-missing
    
  4. Format code:

    uv run black src/ tests/
    
  5. Lint code:

    uv run ruff check src/ tests/
    
  6. Type checking:

    uv run mypy src/
    

Building and Publishing

Build the Package

# Build distribution files
uv build

This creates distribution files in the dist/ directory:

  • mcp_system_info-*.whl (wheel file)
  • mcp_system_info-*.tar.gz (source distribution)

Local Testing with uvx

Test the package locally before publishing:

# Test running the command directly from wheel file
uvx --from ./dist/mcp_system_info-*.whl mcp-system-info

# Test with environment variables
SYSINFO_LOG_LEVEL=DEBUG uvx --from ./dist/mcp_system_info-*.whl mcp-system-info

Publishing to PyPI

# Publish to PyPI (requires PyPI account and token)
uv publish

# Or publish to TestPyPI first
uv publish --repository testpypi

Note: You'll need to:

  1. Create a PyPI account at https://pypi.org
  2. Generate an API token in your account settings
  3. Configure uv with your credentials or use environment variables

Environment Configuration

The server supports configuration through environment variables:

Core Settings

  • SYSINFO_CACHE_TTL - Cache time-to-live in seconds (default: 5)
  • SYSINFO_MAX_PROCESSES - Maximum processes to return (default: 100)
  • SYSINFO_ENABLE_TEMP - Enable temperature sensors (default: true)
  • SYSINFO_LOG_LEVEL - Logging level (default: INFO)

Transport Configuration

  • SYSINFO_TRANSPORT - Transport protocol: stdio, sse, or streamable-http (default: stdio)
  • SYSINFO_HOST - Host to bind to for HTTP transports (default: localhost)
  • SYSINFO_PORT - Port to bind to for HTTP transports (default: 8001)
  • SYSINFO_MOUNT_PATH - Mount path for SSE transport (default: /mcp)

Transport Modes

1. STDIO (Default)

# Uses standard input/output - no network port
uv run mcp-system-info

2. SSE (Server-Sent Events)

# HTTP server with real-time streaming
SYSINFO_TRANSPORT=sse SYSINFO_PORT=8001 uv run mcp-system-info
# Server will be available at http://localhost:8001/mcp

3. Streamable HTTP

# HTTP server with request/response
SYSINFO_TRANSPORT=streamable-http SYSINFO_PORT=9000 uv run mcp-system-info

Complete Example:

SYSINFO_TRANSPORT=sse \
SYSINFO_HOST=0.0.0.0 \
SYSINFO_PORT=8001 \
SYSINFO_CACHE_TTL=10 \
SYSINFO_LOG_LEVEL=DEBUG \
uv run mcp-system-info

Usage Examples

Tool Usage

Get CPU Information

# Basic CPU info
{
  "name": "get_cpu_info_tool",
  "arguments": {
    "interval": 1.0,
    "per_cpu": false
  }
}

Get Process List

# Top 10 processes by memory usage
{
  "name": "get_process_list_tool", 
  "arguments": {
    "limit": 10,
    "sort_by": "memory",
    "filter_name": "python"
  }
}

Get Disk Information

# All disk usage
{
  "name": "get_disk_info_tool",
  "arguments": {}
}

# Specific path
{
  "name": "get_disk_info_tool",
  "arguments": {
    "path": "/home"
  }
}

Resource Usage

System Overview

# Request comprehensive system overview
{
  "uri": "system://overview"
}

Process List Resource

# Get top processes resource
{
  "uri": "system://processes" 
}

Integration with Claude Desktop

Adding to Claude Desktop

  1. Locate your Claude Desktop config file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  2. Add the MCP server configuration:

Using uvx (Recommended)

{
  "mcpServers": {
    "system-info": {
      "command": "uvx",
      "args": ["mcp-system-info"],
      "env": {
        "SYSINFO_CACHE_TTL": "10",
        "SYSINFO_LOG_LEVEL": "INFO"
      }
    }
  }
}

For Local Development

{
  "mcpServers": {
    "system-info": {
      "command": "uv",
      "args": [
        "--directory", 
        "/path/to/mcp-system-info", 
        "run", 
        "mcp-system-info"
      ],
      "env": {
        "SYSINFO_TRANSPORT": "stdio",
        "SYSINFO_CACHE_TTL": "10",
        "SYSINFO_LOG_LEVEL": "INFO"
      }
    }
  }
}

For HTTP Transport (SSE)

{
  "mcpServers": {
    "system-info-http": {
      "command": "uvx",
      "args": ["mcp-system-info"],
      "env": {
        "SYSINFO_TRANSPORT": "sse",
        "SYSINFO_HOST": "localhost",
        "SYSINFO_PORT": "8001",
        "SYSINFO_MOUNT_PATH": "/mcp"
      }
    }
  }
}
  1. Restart Claude Desktop to load the new server.

Using with Claude

Once configured, you can ask Claude to:

  • "What's my current CPU usage?"
  • "Show me the top 10 processes using the most memory"
  • "How much disk space is available?"
  • "What's my system uptime?"
  • "Give me a complete system overview"

Testing

Running Tests

# Run all tests
uv run pytest

# Run with verbose output
uv run pytest -v

# Run specific test file
uv run pytest tests/test_tools.py

# Run with coverage report
uv run pytest --cov=system_info_mcp --cov-report=html

Test Structure

  • tests/test_config.py - Configuration validation tests
  • tests/test_tools.py - Tool implementation tests
  • tests/test_resources.py - Resource handler tests
  • tests/test_utils.py - Utility function tests

All tests use mocked dependencies for consistent, fast execution across different environments.

Performance Considerations

  • Caching: Intelligent caching reduces system calls and improves response times
  • Configurable intervals: Adjust cache TTL based on your needs
  • Lazy loading: Temperature sensors and other optional features load only when needed
  • Async support: Built on FastMCP for efficient async operations

Security Features

  • Read-only operations: No system modification capabilities
  • Sensitive data filtering: Command-line arguments are filtered for passwords, tokens, etc.
  • Input validation: All parameters are validated before processing
  • Error isolation: Failures in one tool don't affect others

Platform Support

  • macOS - Full support including temperature sensors on supported hardware
  • Linux - Full support with hardware-dependent sensor availability
  • Windows - Full support with platform-specific optimizations

Troubleshooting

Common Issues

  1. Permission errors: Some system information may require elevated privileges
  2. Missing sensors: Temperature/fan data availability varies by hardware
  3. Performance impact: Reduce cache TTL or limit process counts for better performance

Debug Mode

Enable debug logging for troubleshooting:

SYSINFO_LOG_LEVEL=DEBUG uv run mcp-system-info

Verifying Installation

Test that tools work correctly:

uv run python -c "from system_info_mcp.tools import get_cpu_info; print(get_cpu_info())"

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes with tests
  4. Run the full test suite
  5. Submit a pull request

Code Standards

  • Follow PEP 8 style guidelines
  • Add type hints to all functions
  • Write tests for new functionality
  • Update documentation as needed

License

[Add your license information here]

Support

[Add support information here]

Recommended Servers

playwright-mcp

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.

Official
Featured
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

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.

Official
Featured
TypeScript
Kagi MCP Server

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.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

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.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured