AI agents call drop_ai_model_endpoint to permanently remove resources in Mcp Oceanbase — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The 'drop' action is a strong indicator of destructive operations that remove resources irreversibly. In OceanBase context, this would delete an AI model endpoint, preventing recovery. While description is empty (lowering confidence slightly), the verb alone justifies Destructive classification over Execute. High severity due to potential business impact if an endpoint serving critical models is removed.
From the tool's definition Tool name 'drop_ai_model_endpoint' uses 'drop' verb, which typically indicates irreversible deletion in database and infrastructure contexts. No description provided to clarify scope.
Documented attack patterns abuse exactly the kind of access drop_ai_model_endpoint gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Oceanbase, and nothing reaches the server without passing your rules. This is the rule we recommend for drop_ai_model_endpoint:
{
"version": "1",
"default": "deny",
"hide": [
"drop_ai_model_endpoint"
]
}drop_ai_model_endpoint 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.
drop_ai_model_endpoint. It is categorised as a Destructive tool in the Mcp Oceanbase MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Mcp Oceanbase MCP server in PolicyLayer and add a rule for drop_ai_model_endpoint: 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 Mcp Oceanbase. Nothing to install.
drop_ai_model_endpoint 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 drop_ai_model_endpoint 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 drop_ai_model_endpoint. 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.
drop_ai_model_endpoint is provided by the Mcp Oceanbase MCP server (oceanbase/awesome-oceanbase-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 134 Mcp Oceanbase tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
134 Mcp Oceanbase tools catalogued and risk-classified — across an index of 42,500+ MCP servers.