detach_from_instance
AI agents use detach_from_instance to create or update resources in Vultr MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Vultr MCP environment.
The name implies detaching a resource (volume, network interface, IP, etc.) from an instance. This is typically a reversible write/modify operation rather than a deletion — the resource still exists but is disassociated. However, detaching could cause service disruption (e.g., detaching a boot volume). Confidence is lowered significantly due to empty description.
From the tool's definition Tool name 'detach_from_instance' suggests removing/detaching a resource from a compute instance. Description is empty and uninformative.
Documented attack patterns abuse exactly the kind of access detach_from_instance gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Vultr MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for detach_from_instance:
{
"version": "1",
"default": "deny",
"tools": {
"detach_from_instance": {
"limits": [
{
"counter": "detach_from_instance_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}detach_from_instance stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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detach_from_instance. It is categorised as a Write tool in the Vultr MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Vultr MCP server in PolicyLayer and add a rule for detach_from_instance: 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 Vultr MCP. Nothing to install.
detach_from_instance is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the detach_from_instance 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 detach_from_instance. 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.
detach_from_instance is provided by the Vultr MCP server (rsp2k/mcp-vultr). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Vultr MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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284 Vultr MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.