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dart-search-mcp

dart-search-mcp

by memorise8
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

search_disclosures

Search corporate disclosures from Korea's DART system by company name, code, date range, disclosure type, and more. Retrieve filing lists with company name, report title, and receipt date.

Instructions

DART 전자공시시스템에서 공시 목록을 검색합니다.

Parameters:
    corp_name: 회사명 (예: "삼성전자", "카카오")
    corp_code: DART 고유번호 (8자리, 예: "00126380")
    bgn_de: 검색 시작일 YYYYMMDD (예: "20240101")
    end_de: 검색 종료일 YYYYMMDD (예: "20241231")
    last_reprt_at: 최종보고서만 검색 (Y/N, 기본값: 빈문자열=전체)
    pblntf_ty: 공시유형
        A=정기공시, B=주요사항보고, C=발행공시, D=지분공시,
        E=기타공시, F=외부감사관련, G=펀드공시, H=자산유동화,
        I=거래소공시, J=공정위공시
    pblntf_detail_ty: 공시상세유형 (공시유형 하위 세부 유형코드)
    corp_cls: 법인구분 (Y=유가증권, K=코스닥, N=코넥스, E=기타)
    sort: 정렬 기준 (date=접수일자, crp=회사명, rpt=보고서명)
    sort_mth: 정렬방식 (asc=오름차순, desc=내림차순)
    page_no: 페이지번호 (기본값: 1)
    page_count: 페이지당 건수 (기본값: 20, 최대 100)

Returns:
    공시 목록 (회사명, 보고서명, 접수일자, 고유번호, 접수번호 포함)
    corp_code를 사용하여 get_company_info() 또는 get_financial_statements()로 상세 조회 가능

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": "search_disclosures"
  }
}

Input Schema

NameRequiredDescriptionDefault
corp_nameNo
corp_codeNo
bgn_deNo
end_deNo
last_reprt_atNo
pblntf_tyNo
pblntf_detail_tyNo
corp_clsNo
sortNodate
sort_mthNodesc
page_noNo
page_countNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It discloses that the tool searches a public system, lists all parameters with explanations, and indicates the return format. It does not mention destructive actions, rate limits, or authentication, but for a read-like search tool, this is sufficient transparency.

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 fairly long due to detailed parameter listing, but it is well-structured: a brief purpose sentence, followed by a parameter list with clear formatting, then return information. Every line adds value, though it could be slightly more concise.

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?

Given the high parameter count and no annotations, the description explains all parameters and return structure, and suggests related tools. It doesn't cover error handling or pagination specifics, but for a search tool with 0 required parameters, it is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description must compensate. It provides detailed explanations for each of the 12 parameters, including examples (e.g., 'corp_name: 회사명 (예: 삼성전자)'). This adds substantial meaning beyond the schema's bare titles and defaults.

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 clearly states it searches the list of disclosures in the DART electronic disclosure system. It specifies the resource (DART system) and the action (searching disclosures), distinguishing it from sibling tools like download_document or get_company_info which serve different purposes.

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

Usage Guidelines3/5

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

The description provides a hint about using corp_code with other tools for detailed info, but lacks explicit guidance on when to use this tool versus alternatives, and does not mention when not to use it. It implies usage for searching disclosures but no clear exclusions or prerequisites.

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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