Etf Flow | AI Builder Hub Review & Alternatives | Flaex AI

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Etf Flow

Safety: 75/100

0.0(0)

Delivers historical crypto ETF flow data, formatted as markdown tables, enabling AI agents to analyze investment trends for BTC and ETH.

MCP ServersData & DatabasesFinance & CryptoDevelopmentSearch & WebCommunicationAI & LLMUtilitiesFreemium

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Overview

Delivers historical crypto ETF flow data, formatted as markdown tables, enabling AI agents to analyze investment trends for BTC and ETH.

This MCP server is relatively safe due to its read-only nature and reliance on historical data. However, users should ensure secure handling of the CoinGlass API key and be aware of potential data inaccuracies from the external API. It is safe to use as long as the API key is secured and the data is validated.

Performance is primarily limited by the CoinGlass API's response time. The server itself performs relatively simple data formatting.

Cost is primarily determined by CoinGlass API usage. Monitor API usage to avoid unexpected charges.

Python7 starsMIT

Connections & Capabilities

Connects To

GitHubDiscord

Capabilities

Read

Client Compatibility

Claude Desktop

full

Cursor

untested

Windsurf

untested

VS Code (Copilot)

untested

Quickstart

Claude Desktop Config

{
  "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" }
    }
  }
}

Tools (1)

safe

get_etf_flow

Fetches historical ETF flow data for BTC or ETH and presents it in a markdown table.

Read-only operation; retrieves and formats existing data.

Security

Auth Method

API Key

Known Risks

!Exposure of the CoinGlass API key.
!Potential for inaccurate data from the CoinGlass API.
!Service disruption if the CoinGlass API is unavailable.
!Lack of rate limiting could lead to API overuse and potential cost implications.

Safety Score

low risk

Positive

+Read-only access to ETF flow data.
+No write or delete operations.
+Data is historical, reducing real-time risk.
+Requires API key for access, adding a layer of authentication.

Risks

-Reliance on a third-party API (CoinGlass) introduces external dependency and potential data integrity issues.
-Improper handling of the CoinGlass API key could lead to unauthorized access.
-Data accuracy depends on the CoinGlass API; inaccuracies could mislead AI agents.
-No built-in rate limiting, potentially leading to API overuse if not managed by the client.

Use Cases

Financial Analysis

-Analyzing historical ETF flow trends to identify investment patterns.
-Predicting future ETF performance based on flow data.
-Comparing ETF flows across different cryptocurrencies (BTC vs. ETH).

AI Agent Decision Making

-Informing AI trading strategies with ETF flow data.
-Guiding AI portfolio allocation based on investment trends.
-Providing AI agents with context for market sentiment analysis.

Research and Reporting

-Generating reports on ETF flow trends for research purposes.
-Creating visualizations of ETF flow data for presentations.
-Supporting academic studies on cryptocurrency investment behavior.

Who Is This For?

Best For

AI agents requiring historical ETF flow data for decision-making.
Financial analysts researching cryptocurrency investment trends.
Researchers studying ETF performance and market sentiment.
Applications needing a simple interface to access ETF flow data.

Not Ideal For

Real-time trading applications requiring up-to-the-second data.
Applications needing write access to ETF data.
Scenarios where data accuracy is paramount and cannot be verified.

Autonomy & Execution

Default ModeRead-only

Sandboxed

The server is read-only, limiting the risk associated with autonomous operation. However, the accuracy of the data depends on the CoinGlass API.

StatelessYes

Retry LogicNot documented

ConcurrencySingle-threaded

Production Tip

Monitor the CoinGlass API for availability and data accuracy. Implement client-side rate limiting to avoid exceeding API usage limits.

FAQ

What data sources does this server use?

This server relies on the CoinGlass API for ETF flow data.

How often is the ETF flow data updated?

The update frequency depends on the CoinGlass API's data availability.

Is an API key required to use this server?

Yes, a CoinGlass API key is required for authentication.

What cryptocurrencies are supported?

Currently, the server supports BTC and ETH ETF flow data.

How is the data formatted?

The data is formatted as a markdown table with ETF tickers as columns and dates as rows.

Can I use this server for real-time trading?

No, this server provides historical data and is not suitable for real-time trading.

What happens if the CoinGlass API is unavailable?

The server will be unable to fetch ETF flow data, and requests will likely fail.

Key Features

Data & Databases Finance & Crypto Development Search & Web Communication AI & LLM Utilities

MCP Server Protocol - Enables seamless integration with AI agents and LLM-powered development environments.

Historical Data Retrieval - Provides long-term flow records for longitudinal investment trend analysis.

Markdown Table Formatting - Delivers data in a structured, human-readable, and AI-parsable format for direct context injection.

BTC/ETH Focused - Specifically targets the most liquid and institutionalized crypto assets for high-relevance analytics.

Automated Data Delivery - Streamlines the pipeline from raw financial records to actionable AI-driven insights.

Use Cases & Problems Solved

Use Cases

•Use when developing autonomous AI financial agents that track institutional capital movement in BTC/ETH spot ETFs.
•Perfect for building automated research dashboards that require real-time historical flow data formatted as markdown tables.
•Ideal if you need to feed structured crypto market sentiment data into an LLM for predictive investment analysis.
•Great for developers creating custom financial notification bots that alert users to significant daily ETF inflow or outflow spikes.
•Use when backtesting crypto trading strategies that rely on the correlation between ETF liquidity and asset price volatility.
•Perfect for integrating live institutional flow reporting into technical analysis frameworks using the Model Context Protocol (MCP).

Problems Solved

✓Eliminates the need for manual scraping of financial news sites for daily crypto ETF flow data.
✓Reduces the complexity of data normalization by providing pre-formatted markdown tables ready for LLM consumption.
✓Solves the lack of standard API accessibility for historical institutional Bitcoin and Ethereum ETF flow information.
✓Removes the friction of integrating external financial data sources into AI agent architectures.

Who It's For

Crypto quantitative researchersAI agents developersFinancial data analystsPython developers building MCP-compatible toolsBlockchain fintech software engineers

Metrics

Discovered2/14/2026

Reviews0

Saved By0 users

Etf Flow

Overview

Connections & Capabilities

Connects To

Capabilities

Client Compatibility

Quickstart

Claude Desktop Config

Tools (1)

Security

Safety Score

Positive

Risks

Use Cases

Financial Analysis

AI Agent Decision Making

Research and Reporting

Who Is This For?

Best For

Not Ideal For

Autonomy & Execution

FAQ

What data sources does this server use?

How often is the ETF flow data updated?

Is an API key required to use this server?

What cryptocurrencies are supported?

How is the data formatted?

Can I use this server for real-time trading?

What happens if the CoinGlass API is unavailable?

Key Features

Use Cases & Problems Solved

Use Cases

Problems Solved

Who It's For

Metrics

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