MCPSERV.CLUB
kukapay

Hyperliquid WhaleAlert MCP

MCP Server

Real‑time whale alerts for Hyperliquid positions over $1M

Stale(55)
7stars
1views
Updated 12 days ago

About

A Python MCP server that pulls large‑value position data from Hyperliquid via CoinGlass, formats it into Markdown tables, and summarizes whale activity for quick insights.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview

Hyperliquid WhaleAlert MCP is a real‑time monitoring service that surfaces whale transactions on the Hyperliquid derivatives platform. By flagging positions whose notional value exceeds $1 million, the server delivers high‑impact market data that would otherwise be buried in raw blockchain feeds. For developers building AI assistants, this means instant access to a curated stream of market movers without the need for custom blockchain parsing or complex data pipelines.

The server exposes two primary capabilities: a tool called and a prompt named . The tool pulls the latest whale events from CoinGlass, formats them into a Markdown table using Pandas for readability, and returns the result directly to the assistant. The prompt leverages the tool’s output to generate concise summaries, highlighting total position value, key symbols involved, and any notable actions such as closing large positions. Together, they provide both raw data and actionable insights in a single API call.

Key features include:

  • Real‑time alerts: Fetches whale transactions as soon as they are reported by CoinGlass, ensuring the assistant can respond to market shifts instantly.
  • Markdown formatting: Output is already styled for display in chat interfaces, reducing the need for additional rendering logic.
  • Python‑friendly: Built on Python 3.10+ and packaged with uv, the server is lightweight yet powerful enough for production use.
  • Extensible prompts: Developers can build on to create more advanced analytics, such as trend detection or risk scoring.

Typical use cases span a wide range of AI‑powered trading tools. A portfolio manager’s assistant can query to surface large position changes before they move markets, allowing the manager to adjust hedges proactively. A compliance bot might flag high‑value trades for audit, while a market research assistant can summarize whale activity to inform newsletters or alerts. Because the MCP server integrates seamlessly with Claude Desktop and other LLM clients, developers can embed these capabilities into existing workflows without rewriting data ingestion logic.

What sets Hyperliquid WhaleAlert MCP apart is its focus on a niche yet critical market segment—whale activity on a popular derivatives exchange. By offering a ready‑made, well‑documented MCP that handles authentication, data fetching, and formatting, it removes a significant barrier to entry for developers looking to enrich their AI assistants with high‑frequency market intelligence.