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mark3lim

db-query-mcp

by mark3lim

get_management_commands

Returns exact terminal commands so users can add, edit credentials, rename aliases, or delete database connections, with guidance for manual execution.

Instructions

사용자가 DB 연결을 추가/삭제하거나, 접속 정보(ID·PW·host 등)를 변경하거나, 별칭을 수정하려고 할 때 호출한다. 이런 작업은 보안상 AI(MCP)가 직접 수행할 수 없고 사용자가 터미널에서 직접 실행해야 한다. 이 도구가 반환한 명령어를 사용자에게 그대로 안내하라. 임의로 명령어를 지어내지 말 것.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskNo안내할 작업: add(연결 추가) / edit_credentials(접속정보 변경) / rename_alias(별칭 수정) / delete(연결 삭제) / all(전체). 생략 시 all.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.6/5.0
Behavior4/5

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 discloses that the tool does not perform the action itself but returns commands for the user to run, and it warns against fabricating commands. It could add more detail about the output format (e.g., whether it returns a list of commands or a single string), but the core behavioral trait is clearly disclosed.

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 concise and front-loaded: it states the trigger condition, the security rationale, and the required agent behavior in three sentences. Every sentence earns its place, and there is no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one optional parameter and no output schema, the description is quite complete. It explains the purpose, the security constraint, and the expected agent behavior. It could be slightly more explicit about what the return value looks like (e.g., a list of commands), but given the simplicity of the tool, this is a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single parameter has a clear enum with descriptions. The description adds context by explaining the overall purpose of the task parameter (which operation the user wants), but the schema already covers the parameter well. The description's mention of the five task types aligns with the enum, so it adds modest value beyond the schema.

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 states a specific purpose: it returns terminal commands for DB connection management tasks (add/delete/edit credentials/rename alias) that the AI cannot perform directly. It clearly distinguishes itself from siblings like list_connections or run_select_query by focusing on generating user-facing commands rather than executing operations.

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

Usage Guidelines5/5

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

The description explicitly states when to use it (when the user wants to add/delete/modify DB connections or aliases) and why (security: AI cannot perform these directly). It also instructs the agent to present the returned commands verbatim and not to invent commands, which is clear usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.