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dqj1998

Japan Company Info — MCP Server (Free Edition)

by dqj1998
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edinet_financials_usgaap

Retrieve official EDINET statutory financials (income statement, balance sheet, cash flow) and executive compensation for a Japanese listed company, with accounting concepts normalized across J-GAAP, US GAAP, and IFRS.

Instructions

Retrieve official EDINET statutory financials (income statement, balance sheet, cash flow) and executive compensation for a Japanese listed company, with accounting concepts normalized across J-GAAP, US GAAP, and IFRS. Runs fully offline on the local machine — no data leaves the host; the requested metric is internally mapped to its Japanese accounting term before searching, and results return as ranked records (company name, 13-digit corporate number, fiscal year, and the requested line items with values in ¥ millions) sourced from 有価証券報告書 XBRL filings. This Free edition indexes 192 blue-chip companies, so a company outside that set returns the closest available matches rather than an error. Use this for a specific financial figure or statement of a named company (e.g. 'Toyota operating income 2023', '経常利益 in US GAAP'); use japan_company_search to discover an entity first, or japan_corporate_registry for identity and certification data. Identify the company by 13-digit corporate number or 4-digit securities code for the most reliable match; Japanese names resolve better than English.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricNoFinancial metric, as an English GAAP term or a Japanese accounting term (e.g. 'operating_income', 'net_income', '経常利益'). Known English terms are mapped to Japanese automatically; unknown terms are searched as-is.
fiscal_yearNoFiscal year, e.g. 2023. Omit to retrieve the latest available year.
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

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so thoroughly: it discloses the offline/no-data-leaves-host execution, internal metric-to-Japanese mapping, output shape as ranked records with company name and corporate number and ¥ millions, XBRL source, the 192-company limitation, and closest-match rather than error behavior. No annotation is present, but the description gives the agent an accurate behavioral model.

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 dense and front-loaded, with every sentence carrying useful information. It is a long single paragraph, which makes quick scanning slightly harder, but there is no redundancy or fluff; many sentences earn their keep.

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

Completeness5/5

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

For a 3-parameter query tool with no output schema and no annotations, the description covers the input formats, the output format (ranked records, specific fields, ¥ millions), the data source, the limitation to 192 blue-chip companies, and the fallback behavior. An agent has enough to invoke and interpret the result correctly.

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% and the input schema already explains the metric mapping, fiscal_year omission, and company_name identifiers, including the reliability note. The description repeats those facts but does not add new parameter-level meaning, so it stays at the high-coverage baseline.

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 names a specific verb and resource ('Retrieve official EDINET statutory financials ... and executive compensation') and adds accounting-standard normalization context. It also differentiates itself from sibling tools by noting the 192-company index and the closest-match fallback behavior, so an agent can tell it apart from japan_industry_benchmarks and japan_shareholders without inspecting those tools.

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?

It explicitly says when to use it: 'Use this for a specific financial figure or statement of a named company', and directs to alternatives: japan_company_search for entity discovery and japan_corporate_registry for identity/certification data. It also gives identifier guidance (13-digit corporate number or 4-digit securities code) and sets expectations for out-of-index queries.

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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