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ncloud-mcp-server

by sjk4425

ncloud_list_cache_buckets

Read-only

Find Object Storage buckets usable for Cloud DB for Cache backup export by specifying the Cache instance number.

Instructions

List Object Storage buckets available for Cloud DB for Cache backup export

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionCodeNoRegion code (e.g., KR, JPN, SGN)
cloudCacheInstanceNoYesCloud Cache instance number the export will run from

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.15.0
    • addedInput schema / properties / cloudCacheInstanceNo
      Added value: +{
      +  "description": "Cloud Cache instance number the export will run from",
      +  "type": "string"
      +}
    • addedInput schema / required
      Added value: +[
      +  "cloudCacheInstanceNo"
      +]
  2. First observedv1.10.1

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds the specific purpose (available for backup export) which implies filtering by eligibility, but does not disclose other behaviors like pagination, response format, or permission requirements. It adds some context beyond annotations but is minimal.

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

Conciseness5/5

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

The description is a single sentence that immediately states the action and context. It is concise, front-loaded, and free of unnecessary words. Every part earns its place.

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

Completeness4/5

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

For a simple list operation with read-only annotation and no output schema, the description is adequate. It clearly states what is listed and for what purpose. It does not mention pagination or response details, but these are not critical for a straightforward list call. It could be slightly more explicit about the required instance number, but that is implied by the schema.

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

Parameters3/5

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

Schema description coverage is 100%, so both regionCode and cloudCacheInstanceNo are documented. The description does not add any additional meaning to the parameters; it only relates to the overall purpose. With full schema coverage, the baseline is 3, and no extra value is provided.

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

Purpose5/5

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

The description clearly states the tool lists Object Storage buckets for a specific purpose: Cloud DB for Cache backup export. It uses a specific verb (List) and resource (Object Storage buckets), and the context distinguishes it from generic bucket listing tools like ncloud_list_buckets and ncloud_ncs_list_buckets, as well as similar tools for other DB services (e.g., ncloud_list_mssql_buckets).

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

Usage Guidelines4/5

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

The purpose is clear enough to infer when to use it: when you need buckets for Cloud DB for Cache backup export. It does not explicitly name alternatives or state when not to use it, but the specific context and sibling list make the usage scenario obvious. It lacks explicit exclusions but the context is strong.

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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