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dstack

Skill Infrastructure Solid
Works inClaude Code
Solid Scanned — metadata only

Eliminates vendor lock-in for GPU/accelerator workloads by providing a unified API across NVIDIA, AMD, TPU, and Tenstorrent.

Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.

2,214 starsMPL-2.0 (commercial OK)FreeQuick setup

Eliminates vendor lock-in for GPU/accelerator workloads by providing a unified API across NVIDIA, AMD, TPU, and Tenstorrent. Reduces infrastructure provisioning time from weeks to hours across clouds, Kubernetes, and on-premises hardware.

ML teams and infrastructure leads who need to train and deploy models on multiple hardware vendors or cloud providers without rewriting orchestration logic.

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https://github.com/dstackai/dstack

By dstackai

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install dstackai/dstack

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.

First thing to try

After installing, paste this into Claude:

Help me distribute model training across on-prem GPU clusters and cloud instances
CostFree

Trust Signals Auto-scanned

Stars2,214Contributors72Last updated2026-08-18LicenseMPL-2.0 (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-08-18 · scanner vattempted-no-data

Community Pulse Active

Discussed on Hacker News, Reddit

3 mentions across 1 sources

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

catalog_hygiene stale-eval refresh: Scored from trust signals (evidence-eval-v1): 2,214 GitHub stars; 72 contributors; last commit 0d ago; license MPL-2.0.

Things to check

  • Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
4/5
Versatility
5/5
Reliability
5/5
Security
3/5
Overall score4.35 / 5.00 SolidEvaluatedAug 2026
catalog_hygiene stale-eval refresh: Scored from trust signals (evidence-eval-v1): 2,214 GitHub stars; 72 contributors; last commit 0d ago; license MPL-2.0.

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