This record as markdown: /tools/io-github-abhishekkumar2021-github/github-logout.md
What github_logout does on GitHub
AI agents call github_logout to permanently remove resources in GitHub, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why github_logout is rated Critical
Clearing the cached authentication token is an irreversible action in the moment — the token is deleted/removed from the cache and cannot be recovered programmatically. This would disrupt all subsequent GitHub operations requiring authentication, effectively breaking the agent's ability to interact with GitHub until re-authenticated.
From the tool's definition Clear the cached GitHub token
Attacks that exploit this kind of access
The rule that runs github_logout safely
PolicyLayer is an MCP gateway: it sits between your AI agents and GitHub, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For github_logout, this is the rule to start with:
github_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 GitHub, apply this rule, and every github_logout call is checked against it from then on.
Questions about github_logout
Clear the cached GitHub token. It is categorised as a Destructive tool in the GitHub MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the GitHub MCP server in PolicyLayer and add a rule for github_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 GitHub. Nothing to install.
github_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 github_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 github_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.
github_logout is provided by the GitHub MCP server (@abhishekmcp/github). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on GitHub, and thousands of servers like it.
Across the catalogue