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ncloud-mcp-server

ncloud-mcp-server

by sjk4425
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

ncloud_search_metric_list

Read-only

Search available Cloud Insight monitoring metrics by product key, then filter by keyword or dimensions to find metrics for monitoring.

Instructions

Search available monitoring metrics for a specific product in Cloud Insight.

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": {
      "prodKey": "<prodKey>"
    },
    "name": "ncloud_search_metric_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNoKeyword to search metric names
prodKeyYesProduct key (cw_key) to search metrics for
dimValuesNoDimension filters ([{name, value}])
idDimensionsNoidDimension names to query
dimensionsSelectedListNoSearch by specific dimension values ([{name, values[]}])

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv2.0.1
    • addedInput schema / properties / dimValues
      Added value: +{
+  "description": "Dimension filters ([{name, value}])",
+  "items": {
+    "additionalProperties": false,
+    "properties": {
+      "name": {
+        "type": "string"
+      },
+      "value": {
+        "type": "string"
+      }
+    },
+    "required": [
+      "name",
+      "value"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}
    • addedInput schema / properties / dimensionsSelectedList
      Added value: +{
+  "description": "Search by specific dimension values ([{name, values[]}])",
+  "items": {
+    "additionalProperties": false,
+    "properties": {
+      "name": {
+        "type": "string"
+      },
+      "values": {
+        "items": {
+          "type": "string"
+        },
+        "minItems": 1,
+        "type": "array"
+      }
+    },
+    "required": [
+      "name",
+      "values"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}
    • addedInput schema / properties / idDimensions
      Added value: +{
+  "description": "idDimension names to query",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • addedInput schema / properties / query
      Added value: +{
+  "description": "Keyword to search metric names",
+  "type": "string"
+}
  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?

readOnlyHint=true already tells the agent this is a safe read, and the description adds almost nothing beyond that: no result limits, pagination, or whether the search is name-keyword-only versus dimension-based. For a 5-parameter search over a large metric catalog, more behavioral context is warranted.

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?

A single well-formed sentence with the resource and the product scope front-loaded; nothing is wasted, though there is also very little substance to compress.

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 search tool with full schema coverage and annotations covering safety, the description is minimally sufficient. It leaves gaps on routing between monitoring siblings and on result volume/limits, which an agent would want before calling.

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 all five parameters (query, prodKey, dimValues, idDimensions, dimensionsSelectedList) are documented in the schema itself. The description adds no format or semantic detail beyond that, making baseline 3 the correct score.

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 names a specific verb (Search), resource (monitoring metrics), and scope (for a specific product in Cloud Insight), so the agent knows exactly what the call does. It stops short of distinguishing itself from adjacent monitoring siblings such as ncloud_list_metrics_groups or ncloud_query_monitoring_data, which a large tool ecosystem makes valuable.

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?

There is no when-to-use/when-not-to-use guidance and no mention of alternatives, despite many sibling tools touching monitoring metrics and rule groups. Product-scoping is implied by the required prodKey in the schema rather than stated as a usage rule.

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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