proxmox_ai_scaling

AI-powered predictive scaling based on usage patterns

SERVERMCP Proxmox Server SOURCEbsahane/mcp-proxmox

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/bsahane-mcp-proxmox/proxmox-ai-scaling.md

WHAT IT DOES

What proxmox_ai_scaling does on MCP Proxmox Server

AI agents invoke proxmox_ai_scaling to trigger actions in MCP Proxmox Server. 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.

RISK

Why proxmox_ai_scaling is rated High

Predictive scaling dynamically adjusts VM/LXC resources (CPU, memory, instances) based on AI analysis of usage patterns. This triggers external operations — resizing, spinning up or down resources — whose effects depend on the AI's decisions. It is not merely reading data; it actively modifies infrastructure state.

From the tool's definition AI-powered predictive scaling based on usage patterns

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs proxmox_ai_scaling safely

PolicyLayer is an MCP gateway: it sits between your AI agents and MCP Proxmox Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For proxmox_ai_scaling, this is the rule to start with:

proxmox_ai_scaling Rate-limited

proxmox_ai_scaling 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "proxmox_ai_scaling": {
      "limits": [
        {
          "counter": "proxmox_ai_scaling_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect MCP Proxmox Server, apply this rule, and every proxmox_ai_scaling call is checked against it from then on.

FAQ

Questions about proxmox_ai_scaling

What does the proxmox_ai_scaling tool do? +

AI-powered predictive scaling based on usage patterns. It is categorised as a Execute tool in the MCP Proxmox Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on proxmox_ai_scaling? +

Register the MCP Proxmox Server MCP server in PolicyLayer and add a rule for proxmox_ai_scaling: 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 MCP Proxmox Server. Nothing to install.

What risk level is proxmox_ai_scaling? +

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

Can I rate-limit proxmox_ai_scaling? +

Yes. Add a rate_limit block to the proxmox_ai_scaling 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 proxmox_ai_scaling completely? +

Set action: deny in the PolicyLayer policy for proxmox_ai_scaling. 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 proxmox_ai_scaling? +

proxmox_ai_scaling is provided by the MCP Proxmox Server MCP server (bsahane/mcp-proxmox). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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