Remove an Ollama model to free disk space.
AI agents call models_remove to permanently remove resources in Yaver — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | Yes |
Parameters from the server's own tool schema.
An AI agent that decides to call models_remove doesn't hesitate, doesn't double-check, and doesn't stop at one. Whatever it removes from Yaver is gone — there is no undo for destructive operations.
Attacks that exploit this kind of access
Remove an Ollama model to free disk space. It is categorised as a Destructive tool in the Yaver MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
models_remove accepts 1 parameter: name. Required: name. The full parameter table on this page comes from the server's own tool schema.
Register the Yaver MCP server in PolicyLayer and add a rule for models_remove: 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 Yaver. Nothing to install.
models_remove is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the models_remove 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 models_remove. 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.
models_remove is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.