This record as markdown: /tools/io-github-kivanccakmak-yaver/models-remove.md
What models_remove does on Yaver
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.
Why models_remove is rated Critical
The tool permanently deletes Ollama models from storage. This is a destructive operation because removal of model files cannot be undone without re-downloading or rebuilding them. While the blast radius is localized to the dev environment (not production systems), the high confidence reflects the clear destructive intent.
From the tool's definition Tool name 'models_remove' combined with description 'Remove an Ollama model to free disk space' indicates irreversible deletion of data (the model files).
Attacks that exploit this kind of access
The rule that runs models_remove safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For models_remove, this is the rule to start with:
models_remove is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Yaver, apply this rule, and every models_remove call is checked against it from then on.
Questions about models_remove
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.
More on Yaver, and thousands of servers like it.
Across the catalogue