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kkawailab

MLIT Data Platform MCP Server

by kkawailab

get_data_catalog_summary

Retrieve basic catalog information (IDs and titles) from Japan's MLIT Data Platform to quickly browse available datasets before accessing detailed metadata.

Instructions

データカタログ・データセットの基本情報(ID、タイトル)を取得する。

            使い方:
            - すべてのカタログのIDとタイトル一覧を取得: 引数なし(内部的に IDs=null 相当)
            - 特定カタログだけの基本情報を取得: 「get_data_catalog」を minimal=True で使うか、こちらのサマリーを利用

            例:
            - 全カタログのID/タイトル:
            (引数なしで呼び出し)

            - 特定ID群のみの概要を見たい(軽量):
            get_data_catalog を minimal=True, ids=["cals","rsdb"] で代用

            注意:
            - 返却内容はID/タイトル中心の軽量情報です。詳細なメタデータやデータセット一覧が必要な場合は「get_data_catalog」を使用してください。
            - 公式APIでは IDs=null を指定すると全件取得になります(本ツールは内部でこの挙動に合わせています)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The actual implementation of get_data_catalog_summary in the MLITClient, which executes the GraphQL query to fetch the data catalog summary.
    async def get_data_catalog_summary(self) -> Dict[str, Any]:
        q = """
        query {
          dataCatalog(IDs: null) {
            id
            title
          }
        }
        """.strip()
        return await self.post_query(q)
  • src/server.py:408-426 (registration)
    The MCP tool registration for 'get_data_catalog_summary' in the server.py file.
        name="get_data_catalog_summary",
        description="""データカタログ・データセットの基本情報(ID、タイトル)を取得する。
    
            使い方:
            - すべてのカタログのIDとタイトル一覧を取得: 引数なし(内部的に IDs=null 相当)
            - 特定カタログだけの基本情報を取得: 「get_data_catalog」を minimal=True で使うか、こちらのサマリーを利用
    
            例:
            - 全カタログのID/タイトル:
            (引数なしで呼び出し)
    
            - 特定ID群のみの概要を見たい(軽量):
            get_data_catalog を minimal=True, ids=["cals","rsdb"] で代用
    
            注意:
            - 返却内容はID/タイトル中心の軽量情報です。詳細なメタデータやデータセット一覧が必要な場合は「get_data_catalog」を使用してください。
            - 公式APIでは IDs=null を指定すると全件取得になります(本ツールは内部でこの挙動に合わせています)。""",
        inputSchema={"type": "object", "properties": {}},
    ),
  • The tool invocation handler in src/server.py that routes the 'get_data_catalog_summary' tool call to the client implementation.
    elif name == "get_data_catalog_summary":
        data = await client.get_data_catalog_summary()
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that returns are 'ID/タイトル中心の軽量情報' (lightweight ID/title-focused info), explains the internal API behavior matching 'IDs=null', and clarifies what is NOT returned (detailed metadata/dataset lists). Minor gap: lacks pagination or exact return structure details.

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 uses clear structural sections (使い方/Usage, 例/Examples, 注意/Notes) that front-load the purpose statement. While the Japanese formatting with indentation consumes space, every sentence provides actionable guidance or behavioral context without redundancy.

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?

Despite having no output schema and no annotations, the description adequately describes the return content qualitatively ('ID/タイトル中心の軽量情報'). It thoroughly covers sibling relationships and usage contexts. Minor gap: lacks exact return value structure specification.

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?

Input schema has 0 parameters, establishing a baseline of 4. The description adds value by explaining the implicit behavior: '引数なし(内部的に IDs=null 相当)' clarifies what happens when called with no arguments, effectively documenting the parameter-less invocation pattern.

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 opening sentence 'データカタログ・データセットの基本情報(ID、タイトル)を取得する' provides a specific verb (取得する/get) and resource (データカタログ・データセット). It clearly distinguishes itself from sibling 'get_data_catalog' by stating that detailed metadata requires that alternative instead.

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 '使い方' section explicitly outlines when to use no arguments (for all catalogs) versus when to use 'get_data_catalog' with minimal=True. The '注意' section explicitly names 'get_data_catalog' as the alternative for detailed metadata needs, providing clear when/when-not guidance.

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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