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ncloud-gov-mcp-server

ncloud-gov-mcp-server

by sjk4425
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

ncloud_query_monitoring_data

Read-only

Retrieve Cloud Insight monitoring metrics by specifying product, metric, and time range. Use intervals and aggregation to analyze performance trends.

Instructions

Query time-series monitoring data from Cloud Insight. Returns metric data for a specific product and metric.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "cw_key": "<cw_key>",
      "prodName": "<prodName>",
      "metric": "<metric>",
      "timeStart": "<timeStart>",
      "timeEnd": "<timeEnd>"
    },
    "name": "ncloud_query_monitoring_data"
  }
}

Input Schema

NameRequiredDescriptionDefault
cw_keyYesProduct key (cw_key) identifying the service (see Cloud Insight metrics)
metricYesMetric name to query (e.g., "avg_cpu_used_rto", "mem_usert")
timeEndYesEnd time in Unix epoch milliseconds
intervalNoAggregation interval (default: Min5)
prodNameYesProduct name (e.g., "System/Server(VPC)")
timeStartYesStart time in Unix epoch milliseconds
dimensionsNoDimension filters as key-value pairs (e.g., {"instanceNo": "12345"})
aggregationNoAggregation type (default: AVG)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

B3.3/5.0
Behavior3/5

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

The `readOnlyHint: true` annotation already indicates this is a safe read operation. The description adds minimal behavioral context beyond stating that it returns metric data, but it does not disclose details such as time-range handling, default aggregation behavior, or any rate limits. It neither contradicts annotations nor adds substantial behavioral insight.

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 two concise sentences that are front-loaded with the primary action. It contains no fluff or redundant detail, and every word contributes to conveying the tool's core function.

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 read-only query tool with full schema coverage, the description is minimally adequate but leaves gaps: it does not describe the return value structure, how to interpret the time-series data, or the relationship between `cw_key` and `prodName`. However, the annotations and schema mitigate the absence of an output schema, so the description is acceptable but not comprehensive.

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% for all parameters, so the schema already documents each field (e.g., `metric` examples, `interval` enums, `dimensions` structure). The description does not add any parameter-specific meaning beyond what the schema provides, so it meets the baseline but does not exceed it.

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 tool queries time-series monitoring data from Cloud Insight for a specific product and metric. It uses a specific verb ('Query') and resource ('time-series monitoring data'), which distinguishes it from many non-monitoring tools, though it does not explicitly differentiate from the closely related sibling `ncloud_query_monitoring_data_multiple`.

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?

The description provides no guidance on when to use this tool versus alternatives such as `ncloud_query_monitoring_data_multiple` or service-specific monitoring tools (e.g., `ncloud_cdss_get_monitoring`, `ncloud_ses_get_monitoring`). There is no mention of exclusions, prerequisites, or scenarios where this tool is the preferred choice.

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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