llm_complete · Universal AI Hub MCP: Risk & Policy

WHAT IT DOES

What llm_complete does on Universal AI Hub

AI agents invoke llm_complete to trigger actions in Universal AI Hub. 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 IT NEEDS A POLICY

Why llm_complete needs a policy

Based on the server context (a multi-LLM gateway) and the tool name 'llm_complete', this tool almost certainly sends prompts to an external LLM provider and returns completions — an external operation whose effects depend on arguments. This qualifies as Execute.

From the tool's definition Tool name 'llm_complete' on a server described as a 'multi-LLM gateway' with 'tool-gated access to AI providers'; description is empty.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

llm_complete Rate-limited

llm_complete 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": {
    "llm_complete": {
      "limits": [
        {
          "counter": "llm_complete_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Universal AI Hub, so you can run agents against it safely.

FAQ

Questions about llm_complete

What does the llm_complete tool do? +

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

How do I enforce a policy on llm_complete? +

Register the Universal AI Hub MCP server in PolicyLayer and add a rule for llm_complete: 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 Universal AI Hub. Nothing to install.

What risk level is llm_complete? +

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

Can I rate-limit llm_complete? +

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

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

llm_complete is provided by the Universal AI Hub MCP server (volkansah/universal-ai-hub). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.