AI agents invoke resume_cluster to trigger actions in Zilliz MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
Based on the tool name, 'resume_cluster' likely triggers the resumption of a paused or stopped cluster, which is an external operational action (starting/restarting infrastructure). This falls under Execute as it triggers an external operation. However, the empty description lowers confidence significantly. Severity is high because resuming a cluster could incur costs or affect running workloads at scale.
From the tool's definition Tool name 'resume_cluster' on a server that manages Zilliz Cloud clusters; description is empty and uninformative.
Documented attack patterns abuse exactly the kind of access resume_cluster gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Zilliz MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for resume_cluster:
{
"version": "1",
"default": "deny",
"tools": {
"resume_cluster": {
"limits": [
{
"counter": "resume_cluster_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}resume_cluster stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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resume_cluster. It is categorised as a Execute tool in the Zilliz MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Zilliz MCP Server MCP server in PolicyLayer and add a rule for resume_cluster: 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 Zilliz MCP Server. Nothing to install.
resume_cluster is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the resume_cluster 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 resume_cluster. 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.
resume_cluster is provided by the Zilliz MCP Server MCP server (zilliztech/zilliz-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 16 Zilliz MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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16 Zilliz MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.