Skip to main content
Glama
kgy0617

ECOS MCP Server

by kgy0617
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

인기 경제지표 즉시 조회

get_popular_statistic
Read-onlyIdempotent

Query key Korean economic indicators by natural-language keyword and receive time-series data directly, bypassing statistical code lookup for ECOS data.

Instructions

한국은행 핵심 경제지표를 코드 검색 없이 단 1번의 호출로 즉시 조회합니다.

사용자가 "기준금리 알려줘", "최근 성장률", "물가상승률 추이" 등을 물을 때
통계표코드나 항목코드를 검색할 필요 없이 즉각적으로 시계열 데이터를 반환합니다.

지원하는 지표 키워드:
- 기준금리 ("기준금리", "금리", "정책금리") — 변경 시점만 반환(changes_only 기본 True)
- 경제성장률 ("경제성장률", "성장률", "GDP성장률") — 실질 GDP 전기비 %
- 국내총생산 ("GDP", "실질GDP", "국내총생산") — 실질 GDP 수준(십억원)
- 소비자물가상승률 ("물가상승률", "인플레이션") — CPI 전년동월비 %(yoy_pct)
- 소비자물가지수 ("CPI", "소비자물가", "물가") — 지수 수준(2020=100)
- 원/달러 환율 ("환율", "원달러", "달러", "USD") — 일별 / ("월평균환율") — 월평균
- 본원통화 ("본원통화", "중앙은행부채")
- M2 광의통화 ("M2", "통화량", "광의통화")
- 국고채 3년 ("국고채", "국고채3년", "채권금리") — 일별 / ("국고채월평균") — 월평균
- 생산자물가지수 ("PPI", "생산자물가")

Args:
    indicator: 조회할 지표명 또는 키워드 (예: "기준금리", "물가상승률", "성장률", "환율")
    recent_years: start_date 미지정 시 최근 몇 년치를 조회할지 (기본: 일별 지표 최근 3개월, 그 외 2년)
    start_date: 검색 시작일 (주기에 맞는 포맷. 미입력 시 자동 계산)
    end_date: 검색 종료일 (미입력 시 현재 시점)
    output_format: "compact"(기본값, 계열별 [시점, 값] 배열), "csv", "json"(ECOS 원본 행)
    transform: "yoy"(전년동기대비 %), "pop"(직전 관측치 대비 %), "none". 미지정 시 지표 기본값 사용
    changes_only: True면 값이 바뀐 시점만 반환. 미지정 시 지표 기본값 사용

Returns:
    핵심 경제지표 시계열 데이터. 결과가 한 번에 다 담기지 않으면 최신 구간을 우선 반환합니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNo
indicatorYes
transformNo
start_dateNo
changes_onlyNo
recent_yearsNo
output_formatNocompact

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds per-indicator defaults (e.g., changes_only 기본 True for 기준금리), output format semantics, and the fallback behavior of returning the latest period if results are too large. This is beyond the annotations and no contradiction exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but organized into distinct sections (overview, supported indicators, Args, Returns) with no redundant prose. Each bullet adds keyword mappings or parameter semantics that are absent from the schema.

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 7 parameters and no output schema, the description covers return formats and behavior. However, it leaves some details vague, such as exact date string formats per frequency and per-indicator defaults for transform/changes_only, so an agent may still need to infer them.

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?

With 0% schema description coverage, the Args section documents all seven parameters, including defaults for recent_years, output_format, and allowed transform values. It also maps indicator keywords to their meanings, which the raw schema cannot convey.

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 immediately states it retrieves Bank of Korea core economic indicators in a single call without code lookup ('코드 검색 없이'), and enumerates the supported indicators. This specific verb+resource framing clearly differentiates it from sibling tools that search statistics tables or items.

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

Usage Guidelines4/5

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

It explicitly says to use this tool when users request popular indicators like 기준금리, 성장률, or 물가상승률, eliminating the need to search codes. However, it never names sibling tools or states when not to use it, so the guidance is contextual but not exclusionary.

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

Deploy Server

Other Tools