AI agents call pyp6xer_clear_cache to permanently remove resources in PyP6Xer MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The name 'clear_cache' strongly suggests this tool deletes cached data, which is typically irreversible. The description is empty, which lowers confidence, but cache-clearing operations are by nature destructive (data cannot be recovered once the cache is purged). Given the context of a schedule analysis tool, cached data could include processed XER file data or analysis results.
From the tool's definition Tool name: pyp6xer_clear_cache — 'clear' in the name implies irreversible deletion of cached data.
Documented attack patterns abuse exactly the kind of access pyp6xer_clear_cache gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and PyP6Xer MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for pyp6xer_clear_cache:
{
"version": "1",
"default": "deny",
"hide": [
"pyp6xer_clear_cache"
]
}pyp6xer_clear_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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pyp6xer_clear_cache. It is categorised as a Destructive tool in the PyP6Xer MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the PyP6Xer MCP Server MCP server in PolicyLayer and add a rule for pyp6xer_clear_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 PyP6Xer MCP Server. Nothing to install.
pyp6xer_clear_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 pyp6xer_clear_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 pyp6xer_clear_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.
pyp6xer_clear_cache is provided by the PyP6Xer MCP Server MCP server (paulieb89/pyp6xer-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from PyP6Xer MCP Server, 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.
29 PyP6Xer MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.