update_model_config · Llauncher MCP: Risk & Policy

WHAT IT DOES

What update_model_config does on Llauncher

AI agents use update_model_config to create or update resources in Llauncher — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Llauncher environment.

WHY IT NEEDS A POLICY

Why update_model_config needs a policy

This tool modifies existing model configurations reversibly. While it changes system state, it does not delete data (which would be Destructive), execute arbitrary code (Execute), or involve financial transactions (Financial). The severity is medium rather than low because misuse could misconfigure inference servers affecting their functionality, and the change is persistent but reversible via subsequent updates.

From the tool's definition Tool name 'update_model_config' with description 'Update an existing model' indicates modification of configuration data. The verb 'update' and context of model configuration management explicitly performs a write operation on model state.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_model_config Rate-limited

update_model_config stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "update_model_config": {
      "limits": [
        {
          "counter": "update_model_config_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

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

FAQ

Questions about update_model_config

What does the update_model_config tool do? +

Update an existing model. It is categorised as a Write tool in the Llauncher MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_model_config? +

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

What risk level is update_model_config? +

update_model_config is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit update_model_config? +

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

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

update_model_config is provided by the Llauncher MCP server (shanevcantwell/llauncher). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.