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e-Stat MCP

e-Stat MCP

by koizumikento
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_dataset

Read-only

Retrieve datasets from Japan's e-Stat government statistics API. Specify a dataset ID to fetch specific data, or omit it to list available datasets.

Instructions

データセットを参照する.

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": "get_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo取得件数
dataset_idNo取得対象のデータセットID（省略時は利用可能一覧）
start_positionNoデータ取得開始位置

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.4.0
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / dataset_id / description
      Added value: +"取得対象のデータセットID（省略時は利用可能一覧）"
    • addedInput schema / properties / limit / description
      Added value: +"取得件数"
    • addedInput schema / properties / start_position / description
      Added value: +"データ取得開始位置"
  2. First observed

TDQS

C2.1/5.0
Behavior2/5

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

The annotation readOnlyHint=true already signals a safe read operation, and the description does not contradict it. However, the description adds no behavioral context beyond the annotation – it does not disclose whether pagination is supported, what the response contains, or any limitations. With output schema present, the return structure is documented elsewhere, but the description itself contributes nothing beyond the annotation.

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 a single short sentence, which is concise and front-loaded. However, it is under-specified to the point of being unhelpful – brevity is not a substitute for content. It is structured as a minimal phrase but lacks the substance needed for effective tool selection.

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?

Despite having an output schema and readOnly annotation, the description lacks crucial context about what a 'dataset' is in this API, how it relates to sibling tools, and what the agent should expect when calling it. The tool is simple (3 optional params), but even so, the description is inadequate for an agent to confidently choose or invoke this tool over its many alternatives.

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 three parameters (limit, dataset_id, start_position) are documented in the schema. The description adds no additional meaning about parameter usage or relationships. Baseline 3 is appropriate since the schema fully handles parameter semantics.

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

Purpose2/5

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

The description says 'データセットを参照する' ('refer to the dataset'), which is nearly a tautology with the tool name get_dataset. It does not specify whether the tool retrieves a single dataset by ID or lists available datasets, even though the schema indicates both are possible. It also does not differentiate from sibling tools like get_stats_data or get_data_catalog, which likely also fetch datasets.

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

Usage Guidelines1/5

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

No guidance is provided on when to use this tool versus the many sibling tools (get_stats_list, get_meta_info, get_data_catalog, etc.). There is no mention of intended scenarios, alternatives, or exclusions, leaving the agent to guess based solely on the name.

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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