adaptercloud_auth_logout
Log out and clear all stored authentication tokens.
This record as markdown: /tools/burdenoff-adaptercloud-mcp/adaptercloud-auth-logout.md
What adaptercloud_auth_logout does on Adaptercloud
AI agents call adaptercloud_auth_logout to permanently remove resources in Adaptercloud, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why adaptercloud_auth_logout is rated Critical
An AI agent that decides to call adaptercloud_auth_logout doesn't hesitate, doesn't double-check, and doesn't stop at one. Whatever it removes from Adaptercloud is gone. There is no undo for destructive operations.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs adaptercloud_auth_logout safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Adaptercloud, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For adaptercloud_auth_logout, this is the rule to start with:
adaptercloud_auth_logout 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 Adaptercloud, apply this rule, and every adaptercloud_auth_logout call is checked against it from then on.
Questions about adaptercloud_auth_logout
Log out and clear all stored authentication tokens. It is categorised as a Destructive tool in the Adaptercloud MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Adaptercloud MCP server in PolicyLayer and add a rule for adaptercloud_auth_logout: 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 Adaptercloud. Nothing to install.
adaptercloud_auth_logout 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 adaptercloud_auth_logout 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 adaptercloud_auth_logout. 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.
adaptercloud_auth_logout is provided by the Adaptercloud MCP server (@burdenoff/adaptercloud-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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