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Manage GPU inventory, VM lifecycle, billing, SSH keys, and setup recipes.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.Massed-Compute/mcp" MCP server from askskill: Run: claude mcp add 'io-github-massed-compute-mcp' -- npx -y massed-compute-mcp
Developers or researchers can review GPU inventory before training or inference jobs to understand available resources and choose the right configuration.
Ops or engineering teams can use it to inspect and handle VM lifecycle operations, such as checking instance status and performing start, stop, or termination workflows.
When a team needs access setup or environment preparation, it can use SSH key management and setup recipes to organize initial access and provisioning steps.
It is designed for compute and infrastructure management, covering GPU inventory, VM lifecycle, billing, SSH keys, and setup recipes.
Yes. The original description explicitly mentions billing, but the exact billing scope and supported actions are not provided; see the source repository for details.
The provided material does not include installation steps, runtime requirements, or key configuration details. Please see the source repository for specifics.
Connect AI to remote servers via SSH for commands and secure file transfer.
Let AI securely access remote machines for ops, transfer, and tunneling.
Manage remote Linux machines over SSH directly from an AI chat.
Execute SSH commands on remote servers and resume large file transfers.
Aggregate multiple MCP servers into a few fixed tools for AI apps.
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