GPU Server
MCP server for GPU monitoring: nvidia-smi, VRAM, utilization, temperature
What is GPU Server?
GPU Server is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server for gpu monitoring: nvidia-smi, vram, utilization, temperature
MCP server for GPU monitoring: nvidia-smi, VRAM, utilization, temperature
This server falls under the Developer Tools and Monitoring & Observability categories on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- MCP server for GPU monitoring: nvidia-smi, VRAM, utilization
Use Cases
Maintainer
Works with
Installation
PIP
pip install mcp-gpu-serverManual Installation
pip install mcp-gpu-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about GPU Server
What is GPU Server?
GPU Server is a Model Context Protocol (MCP) server that mcp server for gpu monitoring: nvidia-smi, vram, utilization, temperature It connects AI assistants to external tools and data sources through a standardized interface.
How do I install GPU Server?
Install via pip with: pip install mcp-gpu-server. Then configure your AI client to connect to this MCP server.
Which AI clients work with GPU Server?
GPU Server works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is GPU Server free to use?
Yes, GPU Server is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Browse More Developer Tools MCP Servers
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Set Up GPU Server in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use GPU Server?
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