"wgpu" matching MCP servers:

Enables MCP-compatible AI assistants to run Python code on Google Colab GPU/TPU runtimes, supporting accelerators like T4, A100, H100, with background execution and Google Drive integration.

Enables AI agents and their users to submit, route, and monitor training jobs across free-tier GPU clouds (Kaggle, Colab, Lightning, local MPS) through a local daemon that tracks quota, explains routing decisions, and gates long or secret-reading agent jobs behind human approval.

Exposes NVIDIA GPU metrics (info, utilization, VRAM, temperature) via MCP tools for real-time querying from AI assistants.

Enables recording a Wine or macOS program on an Apple silicon Mac and analyzing its GPU usage — GPU milliseconds per frame, frame pacing, FPS and memory — through Instruments' Metal System Trace, and also reads Metal .gputrace captures without Xcode and reports Apple's published GPU family facts. Recording, listing, comparing, and paging through traces and captures are exposed as tools that a shell or an AI coding agent can call directly.

MCP server for AI-controlled GPU VRAM management in ComfyUI, allowing Claude to monitor and control GPU state, manage model offloading, and start/stop ComfyUI.

Enables AI agents to submit GPU job requests, select eligible workers, track execution, and retrieve results via MCP.

Provides a persistent compute queue for AI agents, enabling them to submit hardware-aware GPU jobs, monitor execution, and retrieve results and artifacts across sessions via MCP tools.