spraay_gpu_run
Run AI model inference on GPU via Replicate. Supports image generation (flux-pro, sdxl, ideogram), video generation (wan-video, minimax-video), LLMs (llama-70b, llama-8b, mixtral), audio (whisper transcription, musicgen), and utilities (esrgan upscaling, rembg background removal). Use shortcuts like
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What spraay_gpu_run does on Spraay X402 Mcp
AI agents invoke spraay_gpu_run to trigger actions in Spraay X402 Mcp. 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 spraay_gpu_run is rated High
This tool executes arbitrary AI model inference jobs on external GPU infrastructure (Replicate). While not destructive or financial in itself, it triggers external computational operations whose effects depend on the model selection and input parameters provided by the caller. An agent could use this to generate malicious content, perform unauthorized computation at cost, or consume resources.
From the tool's definition Tool description states 'Run AI model inference on GPU via Replicate' and explicitly lists execution capabilities including image generation, video generation, LLMs, audio processing, and upscaling.
Attacks that exploit this kind of access
The rule that runs spraay_gpu_run 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_run, this is the rule to start with:
spraay_gpu_run stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. 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_run call is checked against it from then on.
Questions about spraay_gpu_run
Run AI model inference on GPU via Replicate. Supports image generation (flux-pro, sdxl, ideogram), video generation (wan-video, minimax-video), LLMs (llama-70b, llama-8b, mixtral), audio (whisper transcription, musicgen), and utilities (esrgan upscaling, rembg background removal). Use shortcuts like. It is categorised as a Execute tool in the Spraay X402 Mcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Spraay X402 MCP server in PolicyLayer and add a rule for spraay_gpu_run: 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_run is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the spraay_gpu_run 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_run. 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_run 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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