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ncloud-mcp-server

ncloud-mcp-server

by sjk4425
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

ncloud_list_mssql_log_files

Read-only

List database log files for a Cloud DB for MSSQL server instance using its instance number. Access logs to troubleshoot and audit database activity.

Instructions

List log files for a Cloud DB for MSSQL server instance

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": {
      "cloudMssqlServerInstanceNo": "<cloudMssqlServerInstanceNo>"
    },
    "name": "ncloud_list_mssql_log_files"
  }
}

Input Schema

NameRequiredDescriptionDefault
cloudMssqlServerInstanceNoYesCloud MSSQL server instance number

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.10.1

TDQS

B3.3/5.0
Behavior2/5

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

The annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. However, the description adds no behavioral details beyond the literal operation—no mention of return format, pagination, filtering, or any side effects. It essentially restates the tool's name, providing minimal additional transparency.

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 a single, short sentence that efficiently conveys the operation. It is front-loaded with the verb 'List' and contains no unnecessary words, making it appropriately concise and well-structured.

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?

The tool is simple with one parameter and a read-only annotation, but the description does not describe the output format or any edge cases (e.g., whether all log files are returned, how results are sorted). Without an output schema, the agent must infer what a 'log file' listing entails. It is adequate for a basic list operation but leaves gaps in expectations.

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 schema provides 100% parameter coverage with the description 'Cloud MSSQL server instance number'. The tool description does not add any additional semantic meaning (e.g., format, constraints, examples) beyond what the schema already offers, so the baseline of 3 applies.

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 'List log files for a Cloud DB for MSSQL server instance' uses a specific verb ('List'), clearly identifies the resource ('log files'), and specifies the target ('Cloud DB for MSSQL server instance'). This distinguishes it from similar sibling tools like ncloud_list_mssql_log_backup_files, which is about log backup files rather than regular log files.

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 offers no guidance on when to use this tool versus alternatives such as ncloud_list_mssql_log_backup_files or ncloud_export_mssql_log. It simply states the action without any contextual usage notes or 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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