Remove a user from the Ludus system. Args: user_id: User ID to remove Returns: Removal result
AI agents call remove_user to permanently remove resources in Ludus FastMCP — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Removing a user is a destructive action that cannot be undone without manual intervention (account recreation). It permanently eliminates user access, credentials, and system state. While not as critical as data destruction across the entire system, it represents irreversible harm to a specific identity and warrants the Destructive category.
From the tool's definition Tool name 'remove_user' and description states it will 'Remove a user from the Ludus system' — this is an irreversible deletion of a user account and all associated data/permissions.
Documented attack patterns abuse exactly the kind of access remove_user gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ludus FastMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for remove_user:
{
"version": "1",
"default": "deny",
"hide": [
"remove_user"
]
}remove_user 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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Remove a user from the Ludus system. Args: user_id: User ID to remove Returns: Removal result. It is categorised as a Destructive tool in the Ludus FastMCP MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Ludus Fast MCP server in PolicyLayer and add a rule for remove_user: 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 Ludus FastMCP. Nothing to install.
remove_user 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 remove_user 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 remove_user. 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.
remove_user is provided by the Ludus Fast MCP server (tjnull/ludus-fastmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 201 Ludus FastMCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
201 Ludus FastMCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.