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ETF 플로우 MCP

AI 에이전트의 의사 결정을 지원하기 위해 암호화폐 ETF 흐름 데이터를 제공하는 MCP 서버입니다.

불화 파이썬특허상태

특징

  • 통합 도구 : get_etf_flow 도구는 BTC 또는 ETH에 대한 과거 ETF 흐름 데이터를 동적으로 가져옵니다.

  • 마크다운 테이블 출력 : 피벗 테이블을 활용하여 ETF 티커를 열로, 날짜를 행으로, 합계 흐름을 총 열로 표현하여 데이터를 표시합니다.

  • 신속한 안내 : 사용자 친화적인 쿼리를 위한 LLM 상호작용을 간소화하는 프롬프트( etf_flow_prompt )가 포함되어 있습니다.

Related MCP server: crypto-portfolio-mcp

필수 조건

  • Python : 버전 3.10 이상.

  • uv : 빠른 Python 패키지 및 프로젝트 관리자( 설치 지침 ).

  • CoinGlass API 키 : CoinGlass 에서 키를 얻습니다.

  • Claude Desktop : 대화형 쿼리를 위한 선택 사항입니다.

  • Git : 저장소를 복제합니다.

설치

  1. 저장소 복제 :

    지엑스피1

  2. uv로 설정 : uv 사용하여 종속성을 설치합니다.

    uv sync

용법

Claude Desktop과 통합

  1. Claude Desktop 구성 : 서버를 claude_desktop_config.json 에 추가합니다(macOS에서는 ~/Library/Application Support/Claude 에 있고 Windows에서는 %APPDATA%\Claude 에 있습니다).

    {
      "mcpServers": {
        "etf-flow-mcp": {
          "command": "uv",
          "args": ["--directory", "/absolute/path/to/etf-flow-mcp", "run", "etf-flow-mcp"],
          "env": { "COINGLASS_API_KEY": "your_coinglass_api_key_here" }
        }
      }
    }

    /absolute/path/to/etf-flow-mcp/cli.py 를 cli.py 의 전체 경로로 바꿉니다.

  2. Claude Desktop을 다시 시작합니다 . Claude Desktop UI에 망치 아이콘이 나타나 서버가 로드되었는지 확인합니다.

  3. 쿼리 예 :

    • "최신 BTC ETF 흐름 데이터를 표로 보여주세요"

    • "ETH ETF 흐름 내역을 확인하세요"

출력 예

  • BTC ETF 흐름 :

    | Date       | GBTC      | IBIT      | FBTC      | ARKB      | BITB      | BTCO     | HODL     | BRRR     | EZBC     | BTCW     | Total     |
    |------------|-----------|-----------|-----------|-----------|-----------|----------|----------|----------|----------|----------|-----------|
    | 2025-04-24 | 0         | 327300000 | 0         | 97700000  | 10200000  | 7750000  | 0        | 0        | 0        | 0        | 442200000 |
    | 2025-04-23 | 0         | 643200000 | 124400000 | 129500000 | -15200000 | 0        | 5300000  | 0        | 0        | 0        | 917700000 |
    | 2025-04-22 | 65100000  | 193500000 | 253800000 | 267100000 | 76700000  | 18300000 | 6500000  | 0        | 10600000 | 0        | 912700000 |
    | 2025-04-21 | 36600000  | 41600000  | 88100000  | 116100000 | 45100000  | 0        | 11700000 | 0        | 10100000 | 0        | 381300000 |
    | 2025-04-18 | 0         | 0         | 0         | 0         | 0         | 0        | 0        | 0        | 0        | 0        | 0         |
  • ETH ETF 흐름 :

    | Date       | ETHE      | GETH     | ETHA      | ETHW     | FETH      | ETHV     | EZET     | CETH     | QETH     | Total     |
    |------------|-----------|----------|-----------|----------|-----------|----------|----------|----------|----------|-----------|
    | 2025-04-24 | -6600000  | 18300000 | 40000000  | 5100000  | 0         | 2600000  | 0        | 4100000  | 0        | 63550000  |
    | 2025-04-23 | 0         | 6400000  | -30300000 | 0        | 0         | 0        | 0        | 0        | 0        | -23900000  |
    | 2025-04-22 | 0         | 0        | 0         | 6100000  | 32700000  | 0        | 0        | 0        | 0        | 38800000  |
    | 2025-04-21 | -25400000 | 0        | 0         | 0        | 0         | 0        | 0        | 0        | 0        | -25400000  |
    | 2025-04-18 | 0         | 0        | 0         | 0        | 0         | 0        | 0        | 0        | 0        | 0         |
    | 2025-04-17 | 0         | 0        | 0         | 0        | 0         | 0        | 0        | 0        | 0        | 0         |

특허

이 프로젝트는 MIT 라이선스 에 따라 라이선스가 부여되었습니다.

Available Tools

1 tool
get_etf_flowA
Fetch historical ETF flow data for BTC or ETH from CoinGlass API and return as a Markdown table.

Parameters:
    coin (str): Cryptocurrency to query ('BTC' or 'ETH').

Returns:
    str: Markdown table with ETF flow data (tickers as columns, dates as rows, with total column).
ParametersJSON Schema
NameRequiredDescriptionDefault
coinYes

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the action ('Fetch') and output format ('Markdown table'), but lacks details on error handling, rate limits, authentication needs, or data freshness. It adequately covers basic behavior but misses advanced operational context.

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 well-structured and front-loaded, with a clear opening sentence followed by specific sections for parameters and returns. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 tool's moderate complexity (single parameter, no output schema, no annotations), the description is mostly complete. It covers purpose, parameters, and return format, but could improve by addressing behavioral aspects like error cases or data limitations, which would enhance completeness for an API-based tool.

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 description adds significant meaning beyond the input schema, which has 0% coverage. It explicitly defines the 'coin' parameter as a string with allowed values ('BTC' or 'ETH') and explains its purpose ('Cryptocurrency to query'), compensating fully for the schema's lack of documentation.

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 the tool's purpose with a specific verb ('Fetch'), resource ('historical ETF flow data'), and scope ('for BTC or ETH from CoinGlass API'). It distinguishes the data source and format, making the function unambiguous even without sibling tools.

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 implies usage context by specifying the cryptocurrency options ('BTC' or 'ETH') and the data source (CoinGlass API), but it does not provide explicit guidance on when to use this tool versus alternatives or any prerequisites. Since there are no sibling tools, the lack of comparative guidance is less critical.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedget_etf_flow

TDQS

A3.9/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is singular and clearly defined.

Naming Consistency5/5

The single tool name 'get_etf_flow' follows a clear verb_noun pattern. Since there are no other tools, consistency is inherently perfect.

Tool Count2/5

One tool is too few for the server's apparent scope of ETF flow data analysis. It lacks complementary tools like historical trends, comparisons, or metadata, making the surface feel thin and incomplete for the domain.

Completeness2/5

The tool set is severely incomplete for ETF flow analysis. It only fetches data for BTC or ETH, missing operations like multi-coin queries, date range filtering, summary statistics, or visualization, which are essential for comprehensive coverage.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

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