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ncloud-mcp-server

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TypeScript
Remote

ncloud_send_monitoring_data

Send custom JSON monitoring data to Cloud Insight for a user-defined cw_key schema; records map metric and dimension fields as key-value pairs.

Instructions

Send custom JSON monitoring data to Cloud Insight for a user-defined schema (cw_key). Each record holds the schema's metric and dimension fields as key-value pairs. (SGN region additionally requires header X-NCP-REGION_NO=7.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesData record (object) or records (array) with the schema's metric/dimension fields, e.g. {"cpu": 1.5, "instanceId": "i-1"}
cw_keyYesProduct key (cw_key) of the custom schema

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv2.0.1
    • addedInput schema / properties / cw_key
      Added value: +{
+  "description": "Product key (cw_key) of the custom schema",
+  "type": "string"
+}
    • addedInput schema / properties / data / anyOf
      Added value: +[
+  {
+    "additionalProperties": {},
+    "type": "object"
+  },
+  {
+    "items": {
+      "additionalProperties": {},
+      "type": "object"
+    },
+    "type": "array"
+  }
+]
    • changedInput schema / properties / data / description
      Previous value: -"Array of data entries to send"New value: +"Data record (object) or records (array) with the schema's metric/dimension fields, e.g. {\"cpu\": 1.5, \"instanceId\": \"i-1\"}"
    • removedInput schema / properties / data / items
      Removed value: -{
-  "additionalProperties": false,
-  "properties": {
-    "dimensions": {
-      "additionalProperties": {
-        "type": "string"
-      },
-      "description": "Dimension key-value pairs identifying the resource",
-      "type": "object"
-    },
-    "metrics": {
-      "description": "Array of metric data points",
-      "items": {
-        "additionalProperties": false,
-        "properties": {
-          "metricGroupId": {
-            "description": "Metric group ID",
-            "type": "string"
-          },
-          "metricGroupItemId": {
-            "description": "Metric group item ID",
-            "type": "string"
-          },
-          "timestamp": {
-            "description": "Timestamp in Unix epoch milliseconds (default: current time)",
-            "type": "number"
-          },
-          "value": {
-            "description": "Metric value",
-            "type": "number"
-          }
-        },
-        "required": [
-          "metricGroupId",
-          "metricGroupItemId",
-          "value"
-        ],
-        "type": "object"
-      },
-      "type": "array"
-    }
-  },
-  "required": [
-    "dimensions",
-    "metrics"
-  ],
-  "type": "object"
-}
    • removedInput schema / properties / data / type
      Removed value: -"array"
    • removedInput schema / properties / prodKey
      Removed value: -{
-  "description": "Product key (cw_key) for the custom schema",
-  "type": "string"
-}
    • changedInput schema / required
      Previous value: -[
-  "prodKey",
-  "data"
-]New value: +[
+  "cw_key",
+  "data"
+]
  2. First observedv1.10.1

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It helpfully discloses a non-obvious behavioral trait (the SGN region requires header X-NCP-REGION_NO=7), which is genuine added context. However, it omits auth requirements, any limits on batch size, idempotency, and error behavior for what is clearly a write operation.

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?

Three tight sentences, front-loaded with the core action, followed by the data-structure clarification and the region-specific caveat. The parenthetical region note earns its place as a non-obvious operational detail; no filler.

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?

There is no output schema and no annotations, so an agent might want more: return/acknowledgement behavior, error conditions, and auth expectations are absent. It does cover purpose, payload shape, and a region constraint, which is enough to attempt a call but not enough to handle failure modes.

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 the schema already documents both parameters, including an example payload for 'data'. The description restates the record structure ('metric and dimension fields as key-value pairs') without adding syntax, ordering, or size guidance beyond the schema. 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?

States a specific verb and resource: 'Send custom JSON monitoring data to Cloud Insight for a user-defined schema (cw_key).' An agent immediately understands this is an ingestion/write operation scoped to a custom schema. It does not, however, differentiate itself from siblings like ncloud_query_monitoring_data or ncloud_create_custom_schema.

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

Usage Guidelines3/5

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

The reference to a 'user-defined schema (cw_key)' implies a prerequisite schema must already exist, and the data-format sentence implies the caller must know the schema's fields. But there is no explicit when-to-use vs. alternatives, no mention of a companion schema-creation tool, and no exclusions.

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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