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ncloud-mcp-server

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TypeScript
Remote

ncloud_query_monitoring_data

Read-only

Query time-series monitoring data from Cloud Insight by product, metric, time range, and dimensions to retrieve metric values for analysis.

Instructions

Query time-series monitoring data from Cloud Insight. Returns metric data for a specific product and metric. The aggregation must match one configured in the product schema.

Input Schema

TableJSON 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: Min1)
timeStartYesStart time in Unix epoch milliseconds
dimensionsYesDimensions identifying the resource as key-value pairs (required, e.g., {"instanceNo": "12345"})
aggregationNoAggregation type (default: AVG)
productNameNoProduct name (e.g., "System/Server(VPC)")
queryAggregationNoHow to aggregate query results when the query interval is coarser than stored data (default: AVG)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv2.0.1
    • changedInput schema / properties / aggregation / enum
      Previous value: -[
-  "AVG",
-  "MIN",
-  "MAX",
-  "SUM",
-  "COUNT"
-]New value: +[
+  "COUNT",
+  "SUM",
+  "MAX",
+  "MIN",
+  "AVG"
+]
    • changedInput schema / properties / dimensions / description
      Previous value: -"Dimension filters as key-value pairs (e.g., {\"instanceNo\": \"12345\"})"New value: +"Dimensions identifying the resource as key-value pairs (required, e.g., {\"instanceNo\": \"12345\"})"
    • changedInput schema / properties / interval / description
      Previous value: -"Aggregation interval (default: Min5)"New value: +"Aggregation interval (default: Min1)"
    • removedInput schema / properties / prodName
      Removed value: -{
-  "description": "Product name (e.g., \"System/Server(VPC)\")",
-  "type": "string"
-}
    • addedInput schema / properties / productName
      Added value: +{
+  "description": "Product name (e.g., \"System/Server(VPC)\")",
+  "type": "string"
+}
    • addedInput schema / properties / queryAggregation
      Added value: +{
+  "$ref": "#/properties/aggregation",
+  "description": "How to aggregate query results when the query interval is coarser than stored data (default: AVG)"
+}
    • changedInput schema / required
      Previous value: -[
-  "cw_key",
-  "prodName",
-  "metric",
-  "timeStart",
-  "timeEnd"
-]New value: +[
+  "cw_key",
+  "metric",
+  "timeStart",
+  "timeEnd",
+  "dimensions"
+]
  2. First observedv1.10.1

TDQS

C2.9/5.0
Behavior2/5

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

The annotations provide readOnlyHint=true, so safety is covered. However, the description adds little behavioral context beyond what the first sentence implies – it doesn't mention rate limits, response format (e.g., time series array), or data retention constraints. For a query tool, a bit more on return behavior would help.

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 three sentences, front-loaded with the core purpose and a key constraint. It is concise with no wasted words, though it could be slightly more structured (e.g., bullet points for constraints).

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?

Given 9 parameters, nested dimensions, and no output schema, the description is somewhat sparse. It doesn't explain the expected return format or how to handle pagination, but it does cover the essential purpose and one key constraint. For the complexity, a bit more detail would be beneficial.

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%, meaning every parameter is documented in the schema itself. The description adds a constraint about aggregation matching the product schema, which is a helpful cross-parameter note, but doesn't explain parameter semantics beyond that. Baseline 3 is appropriate.

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 states a specific verb+resource (query time-series monitoring data) and specifies it returns metric data for a product and metric. It clearly distinguishes from siblings like ncloud_send_monitoring_data or ncloud_query_monitoring_data_multiple, though it doesn't explicitly name the latter.

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 explicit when-to-use guidance or alternatives are mentioned. The agent must infer from the context that this is for querying single metric data, but the description doesn't say when to use this versus ncloud_query_monitoring_data_multiple or other monitoring tools.

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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