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Zilliz MCP Server

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by zilliztech

suspend_cluster

Suspend a Zilliz Cloud cluster to pause computing costs while maintaining data storage. Specify the cluster ID to initiate suspension.

Instructions

Suspend a dedicated cluster in Zilliz Cloud.

Args:
    cluster_id: ID of the cluster to suspend
Returns:
    Dict containing cluster suspension info
    Example:
    {
        "cluster_id": "inxx-xxxxxxxxxxxxxxx",
        "prompt": "Successfully Submitted. The cluster will not incur any computing costs when suspended. You will only be billed for the storage costs during this time."
    }
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_idYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions cost implications ('will not incur any computing costs... only billed for storage costs'), which is valuable context beyond basic functionality. However, it lacks details about permissions required, whether suspension is reversible, time to suspend, or error conditions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections for Args and Returns, and the core purpose is stated upfront. However, the example in the Returns section is somewhat verbose and could be more concise while still being informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description does an adequate job explaining the basic operation and cost implications. However, it lacks important context about prerequisites, side effects, error handling, and how to verify suspension status, leaving gaps for an AI agent to operate safely.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explicitly documents the single parameter 'cluster_id' with a clear explanation ('ID of the cluster to suspend'), adding essential meaning beyond the bare schema. Since there's only one parameter, this is sufficient for good understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('suspend') and resource ('dedicated cluster in Zilliz Cloud'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'resume_cluster' or 'describe_cluster' beyond the obvious verb difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives like 'resume_cluster' or 'describe_cluster', nor are there any prerequisites, conditions, or warnings about when suspension is appropriate. The description assumes the user already knows when suspension is needed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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