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ncloud-mcp-server

ncloud-mcp-server

by sjk4425
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

ncloud_dataforest_check_account_name

Read-only

Check whether a Data Forest account name is available and valid, confirming it follows required lowercase, number, and hyphen constraints.

Instructions

Check Data Forest account name availability and validity

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": {
      "name": "<name>"
    },
    "name": "ncloud_dataforest_check_account_name"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesAccount name (lowercase + numbers + '-', 2-16 chars)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.10.1

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the agent knows it's a read operation. The description adds that it checks availability and validity, which is consistent and slightly expands on what 'check' entails. No contradictions found.

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 a single short sentence that efficiently conveys the tool's purpose. It is concise without being too terse, but lacks structured detail (e.g., expected return value).

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 simple validation tool with one parameter and readOnlyHint annotation, the description covers the basic purpose. However, it omits what the tool returns (e.g., boolean or result object), which would help the agent understand the output. Since there is no output schema, this gap matters.

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?

The input schema provides full description for the 'name' parameter (format constraints). The tool description does not add any additional semantic meaning beyond what the schema already conveys. With 100% schema coverage, baseline of 3 is appropriate.

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 checks both availability and validity of Data Forest account names. It uses a specific verb ('Check') and resource ('Data Forest account name'), and distinguishes from sibling tools like `ncloud_dataforest_check_app_name` which likely checks app names.

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 (e.g., other Data Forest check tools or creation tools). It does not mention prerequisites or context for checking availability.

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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