Remove all pending URLs from the documentation processing queue. Use this to reset the queue when you want to start fresh, remove unwanted URLs, or cancel pending processing. This operation is immediate and permanent - URLs will need to be re-added if you want to process them later. Returns the n...
AI agents call clear_queue to permanently remove resources in Ragdocs — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
An AI agent that decides to call clear_queue doesn't hesitate, doesn't double-check, and doesn't stop at one. Whatever it removes from Ragdocs is gone — there is no undo for destructive operations.
Documented attack patterns abuse exactly the kind of access clear_queue gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ragdocs, and nothing reaches the server without passing your rules. This is the rule we recommend for clear_queue:
{
"version": "1",
"default": "deny",
"hide": [
"clear_queue"
]
}clear_queue disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.
Free to start. No card required.
Remove all pending URLs from the documentation processing queue. Use this to reset the queue when you want to start fresh, remove unwanted URLs, or cancel pending processing. This operation is immediate and permanent - URLs will need to be re-added if you want to process them later. Returns the number of URLs that were cleared from the queue. It is categorised as a Destructive tool in the Ragdocs MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Ragdocs MCP server in PolicyLayer and add a rule for clear_queue: 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 Ragdocs. Nothing to install.
clear_queue 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 clear_queue 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 clear_queue. 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.
clear_queue is provided by the Ragdocs MCP server (sanderkooger/mcp-server-ragdocs). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 7 Ragdocs tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
7 Ragdocs tools catalogued and risk-classified — across an index of 42,500+ MCP servers.