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dqj1998

Japan Company Info — MCP Server (Free Edition)

japan_shareholders

Retrieve the major shareholders and ownership structure of a Japanese listed company from its EDINET 有価証券報告書 filing. Runs fully offline and returns a ranked list of top shareholders (name, shares held, ownership percentage) together with…

Instructions

Retrieve the major shareholders and ownership structure of a Japanese listed company from its EDINET 有価証券報告書 filing. Runs fully offline and returns a ranked list of top shareholders (name, shares held, ownership percentage) together with total shares outstanding, taken from the 大株主 section of the XBRL filing; this Free edition covers 192 blue-chip companies, so out-of-set companies return the nearest matches. Use this for ownership, cap-table, and cross-holding questions; use edinet_financials_usgaap for income-statement or balance-sheet figures, or japan_company_search to discover an entity first. Identify the company by 13-digit corporate number or 4-digit securities code for the most reliable match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoNumber of top shareholders to return. Omit to default to 10.
company_nameYesJapanese or English company name, 13-digit corporate number, or 4-digit securities code. A 13-digit number or Japanese name resolves most reliably.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.0

TDQS

A4.5/5.0
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 several behavioral traits: it runs fully offline, covers 192 blue-chip companies, returns nearest matches for out-of-set companies, and explains the return format (ranked list of shareholders with name, shares, ownership percentage, and total shares outstanding). It does not cover error handling or authentication, but for a read-only lookup tool the provided details are adequate. A score of 4 reflects strong disclosure without reaching full completeness.

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 is moderately long but every sentence adds value. It leads with the core purpose, then details the return content and coverage limitation, then gives usage guidance and matching advice. The structure is logical and front-loaded, with no redundant or filler sentences. It could be tightened slightly, but it remains efficient and clear.

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 two parameters, no output schema, and no annotations, the description covers the essential aspects: what it does, what it returns, its limitations (192-company coverage), and how to specify the target company. It also names the relevant sibling tools for adjacent questions. Missing details like error handling or behavior when no match is found are minor for a read-only lookup. Overall, it is sufficiently complete for an agent to call it correctly.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful guidance beyond the schema: it clarifies that company_name can be a Japanese or English name, a 13-digit corporate number, or a 4-digit securities code, and that the numeric forms give the most reliable match. This goes beyond the schema's terse descriptions and helps the agent choose the right input format. top_n is already well described in the schema, so no additional credit needed there.

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 verb ('Retrieve') and a precise resource ('major shareholders and ownership structure of a Japanese listed company from its EDINET 有価証券報告書 filing'), and explicitly names sibling tools it is not (edinet_financials_usgaap for financial statements, japan_company_search for entity discovery). This clearly distinguishes it from the other tools in the list.

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 this tool ('Use this for ownership, cap-table, and cross-holding questions') and names alternatives with their purposes ('use edinet_financials_usgaap for income-statement or balance-sheet figures, or japan_company_search to discover an entity first'). It also provides matching advice (13-digit corporate number or 4-digit securities code for most reliable match), covering both when and how to use it.

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