hyperliquid-whalealert-mcp

Hyperliquid WhaleAlert MCP is an MCP (Model Context Protocol) server designed to provide real-time whale alerts for the Hyperliquid platform. It can flag positions with a notional value exceeding $1 million, helping users track large transaction activity.

Main Capabilities

The server provides one tool and one prompt:

• Tool get_whale_alerts: Retrieves recent whale transactions and returns them as a Markdown table using pandas for clear presentation.
• Prompt summarize_whale_activity: Generates a summary of whale transactions, including metrics such as total position value and notable trading symbols.

Usage

Environment Requirements

• Python 3.10 or higher
• CoinGlass API key (must be obtained from CoinGlass for API access)
• uv package and dependency manager (uv must be installed)

Installation Steps

1. Clone the repository:

   git clone https://github.com/kukapay/hyperliquid-whalealert-mcp.git
   cd hyperliquid-whalealert-mcp
   

2. Install dependencies:

   uv sync
   

   This will install the dependencies specified in pyproject.toml.

Integrating into Claude Desktop

The server can be installed with the following command:

uv run mcp install mcp.py --name "Hyperliquid Whale Alert"

Or manually update the configuration file:

{
  "mcpServers": {
    "hyperliquid-whalealert": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/hyperliquid-whalealert-mcp",
        "run",
        "main.py"
      ],
      "env": {
        "COINGLASS_API_KEY": "your_api_key"
      }
    }
  }
}

Please replace /path/to/hyperliquid-whalealert-mcp with the actual installation path, and replace COINGLASS_API_KEY with your API key.

Calling the Tool

• In MCP Inspector, select get_whale_alerts and execute it.
• In Claude Desktop, use the registered server to call the tool through the UI or API.

Using the Prompt

The summarize_whale_activity prompt can generate a summary of whale transactions. In a compatible client, the prompt can be extended to let the LLM provide detailed metrics such as total position value or notable trading symbols.

Applicable Scenarios

Suitable for users who need to monitor large positions and trading activity on the Hyperliquid platform, such as traders, analysts, or researchers, to quickly obtain whale activity by integrating into an MCP client.

Limitations

• A CoinGlass API key is required to access data.
• Depends on Python 3.10+ and uv.
• The project uses the MIT License; see the LICENSE file for details.