AI agents call delete_context_cache to permanently remove resources in Gpal — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
This tool permanently removes a Gemini context cache without the ability to undo the operation. Context caches may contain important cached computations, embeddings, or session state that an AI agent might inadvertently delete. The irreversible nature and potential loss of work/data justify the Destructive category.
From the tool's definition Tool name includes 'delete' and description states 'Delete a Gemini context cache' — irreversible removal of cached data.
Documented attack patterns abuse exactly the kind of access delete_context_cache gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Gpal, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_context_cache:
{
"version": "1",
"default": "deny",
"hide": [
"delete_context_cache"
]
}delete_context_cache disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.
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Delete a Gemini context cache. It is categorised as a Destructive tool in the Gpal MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Gpal MCP server in PolicyLayer and add a rule for delete_context_cache: 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 Gpal. Nothing to install.
delete_context_cache 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 delete_context_cache 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 delete_context_cache. 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.
delete_context_cache is provided by the Gpal MCP server (tobert/gpal). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Gpal, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
19 Gpal tools catalogued and risk-classified — across an index of 43,000+ MCP servers.