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etf-flow-mcp

by kukapay
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ETF 流量 MCP

MCP 服务器提供加密 ETF 流动数据，为 AI 代理的决策提供支持。

不和谐Python执照地位

特征

  • 统一工具： get_etf_flow工具动态获取 BTC 或 ETH 的历史 ETF 流量数据。

  • Markdown 表输出：利用数据透视表来呈现数据，其中 ETF 代码作为列、日期作为行、总流量作为总列。

  • 提示指导：包括提示（ etf_flow_prompt ）以简化 LLM 交互，实现用户友好的查询。

Related MCP server: crypto-portfolio-mcp

先决条件

  • Python ：版本 3.10 或更高版本。

  • uv ：一个快速的 Python 包和项目管理器（安装说明）。

  • CoinGlass API 密钥：从CoinGlass获取密钥。

  • Claude Desktop ：可选，用于交互式查询。

  • Git ：用于克隆存储库。

安装

  1. 克隆存储库：

    git clone https://github.com/kukapay/etf-flow-mcp.git
cd etf-flow-mcp

  2. 使用 uv 设置：使用uv安装依赖项：

    uv sync

用法

与 Claude Desktop 集成

  1. 配置 Claude 桌面：将服务器添加到claude_desktop_config.json （位于 macOS 上的~/Library/Application Support/Claude或 Windows 上的%APPDATA%\Claude ）：

    {
  "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" }
    }
  }
}

    将/absolute/path/to/etf-flow-mcp/cli.py替换为cli.py的完整路径。

  2. 重新启动 Claude Desktop ：验证 Claude Desktop UI 中是否出现锤子图标以确认服务器已加载。

  3. 查询示例：

    • “以表格形式展示最新的 BTC ETF 流量数据”

    • “获取 ETH ETF 流动历史记录”

示例输出

  • BTC ETF 流向：

    | 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 流量：

    | 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         |

执照

该项目已获得MIT 许可。

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
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

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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