spraay_gpu_status
Check the status of a GPU prediction by ID. Use this to poll for results on longer-running jobs like video generation or large model inference. Returns output when complete. Costs $0.002 USDC.
This record as markdown: /tools/io-github-plagtech-spraay-x402-mcp/spraay-gpu-status.md
What spraay_gpu_status does on Spraay X402 Mcp
AI agents call spraay_gpu_status to retrieve information from Spraay X402 Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why spraay_gpu_status is rated Low
The tool queries the status of an existing GPU prediction job and retrieves results—this is a read-only retrieval operation with no side effects. While it incurs a financial cost ($0.002 USDC), that fee is automatic and not controlled by the agent's arguments; the agent cannot create financial obligations or transfer value.
From the tool's definition Check the status of a GPU prediction by ID... Returns output when complete. Costs $0.002 USDC.
Attacks that exploit this kind of access
The rule that runs spraay_gpu_status safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Spraay X402 Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For spraay_gpu_status, this is the rule to start with:
spraay_gpu_status is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Spraay X402 Mcp, apply this rule, and every spraay_gpu_status call is checked against it from then on.
Questions about spraay_gpu_status
Check the status of a GPU prediction by ID. Use this to poll for results on longer-running jobs like video generation or large model inference. Returns output when complete. Costs $0.002 USDC. It is categorised as a Read tool in the Spraay X402 Mcp MCP Server, which means it retrieves data without modifying state.
Register the Spraay X402 MCP server in PolicyLayer and add a rule for spraay_gpu_status: 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 Spraay X402 Mcp. Nothing to install.
spraay_gpu_status is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the spraay_gpu_status 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.
Set action: deny in the PolicyLayer policy for spraay_gpu_status. 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.
spraay_gpu_status is provided by the Spraay X402 MCP server (spraay-x402-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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