High Risk →

create_prediction

Run a model and get prediction result

Risk signalsExecutes AI model inference

Part of the Replicate server.

create_prediction can trigger actions in Replicate, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke create_prediction to trigger processes or run actions in Replicate. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

create_prediction can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_prediction": {
      "limits": [
        {
          "counter": "create_prediction_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Replicate policy for all 13 tools.

Get this rule live on your own Replicate server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access create_prediction gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so create_prediction only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the create_prediction tool do? +

Run a model and get prediction result. It is categorised as a Execute tool in the Replicate MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on create_prediction? +

Register the Replicate MCP server in PolicyLayer and add a rule for create_prediction: 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 Replicate. Nothing to install.

What risk level is create_prediction? +

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

Can I rate-limit create_prediction? +

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

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

create_prediction is provided by the Replicate MCP server (@mcp-replicate). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Replicate tool call.

Deterministic rules across all 13 Replicate tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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