start_gpu_instance

start_gpu_instance

Server Nebulablock nebula-block-data/nebulablock-mcp-server
Category Execute
Risk class High
Parameters 00 required

What start_gpu_instance does on Nebulablock

AI agents invoke start_gpu_instance to trigger actions in Nebulablock. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

Why start_gpu_instance needs a policy

This tool triggers an external operation that activates cloud infrastructure and incurs costs. While not immediately destructive or financial in itself, starting a GPU instance commits computational resources and billing obligations.

From the tool's definition Tool name 'start_gpu_instance' indicates activation of a computational resource. Combined with sibling tools including 'create_gpu_instance' and 'delete_gpu_instance', this server manages compute infrastructure.

Questions about start_gpu_instance

What does the start_gpu_instance tool do? +

start_gpu_instance. It is categorised as a Execute tool in the Nebulablock MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on start_gpu_instance? +

Register the Nebulablock MCP server in PolicyLayer and add a rule for start_gpu_instance: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Nebulablock. Nothing to install.

What risk level is start_gpu_instance? +

start_gpu_instance is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit start_gpu_instance? +

Yes. Add a rate_limit block to the start_gpu_instance rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block start_gpu_instance completely? +

Set action: deny in the PolicyLayer policy for start_gpu_instance. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides start_gpu_instance? +

start_gpu_instance is provided by the Nebulablock MCP server (nebula-block-data/nebulablock-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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