Skip to main content
Glama
438,654 tools. Updated 2026-08-10 15:41

"PyTorch" matching MCP tools:

Matching MCP Servers

  • Check GPU availability and performance in conda environments for PyTorch or TensorFlow, verifying Metal acceleration setup and providing benchmark comparisons.
    MIT
  • Create a parallel Claude session to execute independent tasks concurrently. Use for background jobs, long-running processes, or when work can be decomposed.
    MIT
  • Check which quantization backends (GGUF, GPTQ, AWQ) are installed, verify PyTorch and transformers availability, and view GPU and RAM details. No arguments required.
    MIT
  • Preserve the current sandbox system state including installed packages as a reusable image. Restore later to replicate the exact environment.
    MIT
  • Summarize PyTorch profiler traces from runs or artifacts, presenting normalized Perfetto evidence. Review execution metrics without extracting data yourself.
    MIT
  • Retrieve ComfyUI server health metrics including version details, memory usage, and device information to monitor system status and resource utilization.
    MIT
  • Retrieve a list of available templates, with options to include official RunPod templates, community public templates, or endpoint-bound templates.
    Apache 2.0
  • Look up an error message in deadends.dev to get known dead ends, workarounds, and next steps. Avoid failed approaches before spending time on fixes across 51 domains.
    MIT
  • Without local embeddings, delegate semantic search to the parent process to query the shared database for notes or dialog.
    MIT
  • Detect AI system usage in a project directory and generate an EU AI Act compliance report that classifies risk level and identifies compliance gaps.
    MIT
  • Provision a GPU or CPU pod on RunPod. Configure image, GPU type, storage, ports, and environment variables for compute workloads.
    Apache 2.0
  • Retrieve details of a specific Kaggle model instance by providing owner, model slug, framework, and instance slug.
    MIT