Unlock the Power of Crypto ETF Data with the ETF Flow MCP Server on UBOS

In today’s rapidly evolving financial landscape, Artificial Intelligence (AI) is increasingly relied upon to make informed decisions. For AI agents operating in the cryptocurrency market, access to timely and accurate data is paramount. The ETF Flow MCP (Model Context Protocol) server, available on the UBOS Asset Marketplace, provides a crucial data feed, delivering crypto ETF flow information to power AI agents’ decision-making processes.

This comprehensive overview explores the ETF Flow MCP server, its features, benefits, integration with the UBOS platform, and its significance in the context of AI-driven financial analysis. We will also delve into the technical aspects of setting up and using the server, providing a detailed guide for both developers and financial analysts.

Understanding the ETF Flow MCP Server

The ETF Flow MCP server is designed to deliver historical crypto ETF flow data, specifically focusing on Bitcoin (BTC) and Ethereum (ETH). It acts as a crucial data source for AI agents, enabling them to analyze market trends, predict future movements, and make data-driven investment decisions. By providing a standardized and easily accessible data feed, the server simplifies the integration of real-world financial data into AI models.

The server utilizes the CoinGlass API to fetch historical ETF flow data. This ensures that the data is reliable, accurate, and up-to-date. The server then processes the data and presents it in a user-friendly format, making it easy for AI agents to consume and interpret.

Key Features:

• Unified Tool: The get_etf_flow tool dynamically fetches historical ETF flow data for BTC or ETH, providing a single point of access for all relevant data.
• Markdown Table Output: The server leverages pivot tables to present data with ETF tickers as columns, dates as rows, and a total column for summed flows, making it easy to visualize and analyze the data.
• Prompt Guidance: Includes a prompt (etf_flow_prompt) to streamline LLM interactions for user-friendly queries, simplifying the process of extracting information from the data.

Use Cases:

• AI-Driven Trading: AI agents can use the ETF flow data to identify trends and patterns, enabling them to make informed trading decisions.
• Risk Management: The data can be used to assess the risk associated with different crypto ETFs, helping investors to manage their portfolios more effectively.
• Market Analysis: Financial analysts can use the data to gain insights into market sentiment and predict future price movements.
• Portfolio Optimization: AI agents can use the ETF flow data to optimize investment portfolios, maximizing returns while minimizing risk.

Integrating with the UBOS Platform

UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department. The platform helps orchestrate AI Agents, connect them with enterprise data, build custom AI Agents with your LLM model, and create Multi-Agent Systems. The ETF Flow MCP server seamlessly integrates with the UBOS platform, providing a valuable data source for AI agents operating within the UBOS ecosystem.

The UBOS Asset Marketplace provides a centralized location for discovering and deploying MCP servers, making it easy to find and integrate the ETF Flow MCP server into your AI projects. The platform also provides tools for managing and monitoring MCP servers, ensuring that they are running smoothly and providing accurate data.

Benefits of Using the ETF Flow MCP Server on UBOS:

• Simplified Integration: The UBOS platform simplifies the process of integrating the ETF Flow MCP server into your AI projects, reducing the time and effort required to get started.
• Centralized Management: The UBOS platform provides a centralized location for managing and monitoring your MCP servers, making it easy to keep track of their status and performance.
• Enhanced Security: The UBOS platform provides a secure environment for running your AI agents and MCP servers, protecting your data from unauthorized access.
• Scalability: The UBOS platform is designed to scale to meet the needs of your AI projects, ensuring that you have the resources you need to succeed.

Technical Guide: Setting Up and Using the ETF Flow MCP Server

This section provides a detailed guide on how to set up and use the ETF Flow MCP server. It covers the prerequisites, installation steps, and usage examples.

Prerequisites:

• Python: Version 3.10 or higher.
• uv: A fast Python package and project manager.
• CoinGlass API Key: Obtain a key from CoinGlass.
• Claude Desktop: Optional, for interactive querying.
• Git: For cloning the repository.

Installation:

1. Clone the Repository:

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

2. Set Up with uv:

   Install dependencies using uv:

   bash uv sync

Usage:

Integrating with Claude Desktop

1. Configure Claude Desktop:

   Add the server to claude_desktop_config.json (located in ~/Library/Application Support/Claude on macOS or %APPDATA%Claude on Windows):

   { “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” } } } }

   Replace /absolute/path/to/etf-flow-mcp/cli.py with the full path to cli.py.

2. Restart Claude Desktop:

   Verify the hammer icon appears in the Claude Desktop UI to confirm the server is loaded.

3. Query Examples:

   • “Show me the latest BTC ETF flow data in a table”
   • “Get the ETH ETF flow history”

Example Output:

• BTC ETF Flow:

  markdown

  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 Flow:

  markdown

  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

The Significance of ETF Flow Data for AI Agents

ETF flow data provides valuable insights into market sentiment and investor behavior. By analyzing the flow of funds into and out of crypto ETFs, AI agents can gain a better understanding of market trends and make more informed investment decisions. This data is particularly useful for:

• Identifying Bullish and Bearish Trends: Positive ETF flows indicate increased investor confidence and can signal a bullish trend, while negative flows suggest decreased confidence and a potential bearish trend.
• Predicting Price Movements: By analyzing the relationship between ETF flows and price movements, AI agents can develop models to predict future price changes.
• Gauging Market Sentiment: ETF flow data can be used to gauge overall market sentiment, providing a valuable indicator of investor confidence.

Conclusion

The ETF Flow MCP server on the UBOS Asset Marketplace provides a crucial data feed for AI agents operating in the cryptocurrency market. By delivering timely and accurate ETF flow data, the server enables AI agents to make more informed decisions, manage risk more effectively, and optimize investment portfolios. With its seamless integration with the UBOS platform and user-friendly interface, the ETF Flow MCP server is an invaluable tool for anyone looking to leverage AI in the world of crypto finance. As UBOS continues to expand its AI Agent Development Platform, the ETF Flow MCP server stands as a testament to the power of combining AI with real-world financial data.