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鉄道駅LOD MCPサーバー

鉄道駅LOD MCPサーバー

by uedayou
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

複数の駅・路線の位置情報をファイルへ書き出し

save_railway_geometries_to_file

Writes multiple railway geometries from addresses to a local GeoJSON file, avoiding response-size limits and including CC BY-SA 4.0 attribution. Use for bulk exports, not for immediate map rendering.

Instructions

get_railway_geometries と同じ複数取得だが、結果を会話に含めずローカルファイルへ直接書き出す。応答サイズの上限を回避できる。出典・ライセンス(CC BY-SA 4.0)を出力に明記する。地図をその場で描く依頼には使わない(中身が会話に返らないため)。

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": {
      "addresses": "<addresses>",
      "outputPath": "<outputPath>"
    },
    "name": "save_railway_geometries_to_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
simplifyNoラインの座標点数を間引くレベル(既定 'none')。ファイル書き出しなので応答サイズ制限は無いが、ファイルサイズや後段ツールの負荷を抑えたいときに指定する。
addressesYesエンティティのラベル or URI の配列(最大50件)。解決ルールは get_railway_geometry と共通。全事業者/全路線のように多い一覧は list_railway_operators / list_railway_children の結果を渡すこと。
outputPathYes書き出し先のファイルパス(相対パスはサーバープロセスのカレントディレクトリ基準、絶対パスも可)。GeoJSON として扱えるよう `.geojson` を推奨。親ディレクトリは自動作成。既存ファイルは上書き。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.2

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full load and does well: it discloses the file-write side effect, that results are excluded from the conversation, the size-limit motivation, and that CC BY-SA 4.0 attribution is embedded in the output. Gaps remain around failure behavior, path/permission constraints, and whether any confirmation is returned, which the schema only partially covers (overwrite and auto-created parent directories).

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?

Four short sentences, front-loaded with the sibling comparison, then the size benefit, the license obligation, and the exclusion. Dense but every sentence carries distinct information; the license sentence is arguably a compliance note rather than invocation guidance but still earns its place.

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 three-parameter tool with no annotations and no output schema, the description covers the essential decision inputs: what it produces, where it goes, why to choose it, and what it must not be used for. Only the shape of the returned value (e.g. a short confirmation vs. nothing) is left unstated.

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%, including the simplify enum, the 50-item address cap, and outputPath semantics, so the description adds no parameter-level meaning beyond what structured fields already provide. Baseline 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?

States a specific verb and resource (write multiple railway geometries to a local file) and immediately anchors it to the sibling get_railway_geometries, noting the single difference: output goes to disk rather than the conversation. An agent can distinguish the two without opening either schema.

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?

Gives both a when-to-use condition (bulk retrieval that would exceed response size limits) and an explicit when-not-to-use rule: requests to render a map inline, because the content never returns to the conversation. It also routes the agent to list_railway_operators / list_railway_children for large enumerations via the schema.

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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