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Personal DB MCP Server

Personal DB MCP Server

by itoufo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

list_custom_entries

Fetch custom entries from your personal database, applying filters, sorting, and pagination to get the data needed for AI context.

Instructions

カスタムエントリ一覧を取得

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_custom_entries"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo取得件数 (デフォルト: 50)
filterNoフィルタ条件 (カラム名: 値)
offsetNoオフセット
order_byNoソートカラム (デフォルト: created_at)
order_descNo降順ソート (デフォルト: true)
profile_idNo対象プロフィール (account-scoped APIキーの場合は必須)。未指定で profile-scoped キーは bind 先プロフィールを使用。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It doesn't mention pagination behavior, output format, whether results are profile-scoped, or any side effects. The description is too minimal to convey behavioral traits beyond 'this lists things'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—a single short phrase. While there is no wasted prose, this level of brevity crosses from 'concise' into 'under-specified'. The short length is appropriate for a tool with 100% schema coverage, but it omits context that could help an agent.

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

Completeness2/5

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

This is a list tool with 6 parameters, 40+ sibling tools including many other list_* tools, no output schema, and no annotations. The description provides no usage context, no return-value expectation, and no distinction from similar list tools. For the complexity and modest schema richness, the description is insufficiently complete.

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 6 parameters are documented in the schema with descriptions (limit default 50, offset, order_by, order_desc, profile_id, filter). The description itself adds no parameter context, but with full schema coverage, the baseline 3 is appropriate. The filter param has a somewhat ambiguous description ('カラム名: 値') but that's schema's responsibility.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'カスタムエントリ一覧を取得' (get custom entry list) states the verb+resource clearly. However, it doesn't distinguish from sibling tools like get_custom_entry (singular) or list_custom_categories, though the plural '一覧' (list) plus 'custom_entry' is fairly clear. It doesn't provide any detail about scoping or what custom entries represent.

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?

No guidance on when to use this tool versus alternatives. There's no comparison to get_custom_entry, list_custom_categories, or search. The description doesn't mention scenarios or limitations, so an agent must infer usage purely from the tool name and sibling context.

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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