Remove GitHub/GitLab onboarding from the local machine or from one or more owned Yaver machines. Can remove clone credentials, CI/deploy vault tokens, or both.
AI agents call machine_onboarding_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 |
|---|---|---|---|
device_id | string | — | Optional remote device ID |
providers | array | — | Providers to remove |
device_ids | array | — | Optional list of owned remote device IDs |
gitlab_host | string | — | Optional specific GitLab host to clear |
remove_clone | boolean | — | Remove clone/pull credentials and provider config (default true) |
remove_ci_token | boolean | — | Remove CI/deploy vault token (default true) |
Parameters from the server's own tool schema.
An AI agent that decides to call machine_onboarding_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 GitHub/GitLab onboarding from the local machine or from one or more owned Yaver machines. Can remove clone credentials, CI/deploy vault tokens, or both. 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.
machine_onboarding_remove accepts 6 parameters: device_id, providers, device_ids, gitlab_host, remove_clone, remove_ci_token. 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 machine_onboarding_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.
machine_onboarding_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 machine_onboarding_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 machine_onboarding_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.
machine_onboarding_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.