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kukapay

hyperliquid-whalealert-mcp

by kukapay
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Remote

Hyperliquid WhaleAlert MCP

An MCP server that provides real-time whale alerts on Hyperliquid, flagging positions with a notional value exceeding $1 million.

GitHub License Python Version Status

Features

  • Tool: get_whale_alerts: Fetches recent whale transactions and returns them as a Markdown table using pandas for clean formatting.

  • Prompt: summarize_whale_activity: Generates a summary of whale transactions, including metrics like total position value and notable symbols.

Related MCP server: hyperliquid-info-mcp

Prerequisites

  • Python: Version 3.10 or higher.

  • CoinGlass API Key: Obtain from CoinGlass (required for API access).

  • uv: Package and dependency manager (install uv).

Installation

  1. Clone the Repository:

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

  2. Install Dependencies:

    uv sync

    This installs dependencies specified in pyproject.toml.

  3. Claude Desktop Integration: Install the server in Claude Desktop:

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

    Or update the configuration file manually:

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

    Replace /path/to/hyperliquid-whalealert-mcp with your actual installation path and COINGLASS_API_KEY with your API key.

Usage

Using the Tool

The get_whale_alerts tool fetches whale transaction data and returns it as a Markdown list. Example output:

- **ETH Transaction**:
  - User Address: 0x3fd4444154242720c0d0c61c74a240d90c127d33
  - Position Size: 12700
  - Entry Price: $1611.62
  - Liquidation Price: $527.2521
  - Position Value (USD): $21003260
  - Action: Close
  - Create Time: 2025-05-20 12:31:57
- **BTC Transaction**:
  - User Address: 0x1cadadf0e884ac5527ae596a4fc1017a4ffd4e2c
  - Position Size: 33.54032
  - Entry Price: $87486.2
  - Liquidation Price: $44836.8126
  - Position Value (USD): $2936421.4757
  - Action: Close
  - Create Time: 2025-05-20 12:31:17

To invoke the tool:

  • In the MCP Inspector, select get_whale_alerts and execute.

  • In Claude Desktop, use the registered server and call the tool via the UI or API.

Using the Prompt

The summarize_whale_activity prompt generates a summary of whale transactions. Example interaction (in a compatible client):

/summarize_whale_activity

Response:

I'll analyze the whale transaction data and provide a summary.

This can be extended by LLMs to provide detailed metrics like total position value or notable symbols.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Available Tools

1 tool
get_whale_alertsB

Fetch recent whale alerts and return as a Markdown table

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but only states the basic action and output format. It misses key behavioral details like rate limits, data source, error handling, or whether it's read-only/destructive, leaving significant gaps for an agent.

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 a single, efficient sentence that front-loads the core functionality ('Fetch recent whale alerts') and adds necessary detail ('return as a Markdown table') without any wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and a tool that fetches data, the description is incomplete. It lacks details on data scope (e.g., time range, number of alerts), error cases, or response structure beyond format, making it inadequate for reliable agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add param info, but with no params, a baseline of 4 is appropriate as it doesn't have to compensate for gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Fetch') and resource ('recent whale alerts'), specifying the output format ('Markdown table'). However, with no sibling tools, it cannot demonstrate differentiation, so it doesn't reach a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool, such as frequency, data freshness, or limitations. The description lacks any context about alternatives or prerequisites, offering only basic functional information.

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. Dates show when Glama detected each change.

  1. 1 tool update
    • First observedget_whale_alerts
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TDQS

B3.2/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as fetching whale alerts, making it distinct by default.

Naming Consistency5/5

The single tool follows a clear verb_noun pattern (get_whale_alerts), which is consistent and predictable. Since there are no other tools to compare against, naming is inherently consistent.

Tool Count2/5

A single tool is too few for the server's apparent purpose of monitoring whale alerts, as it lacks operations like filtering, subscribing, or historical queries. This minimal scope limits functionality and may cause agent failures due to incomplete coverage.

Completeness2/5

The tool surface is severely incomplete for a whale alert system, offering only fetching recent alerts without capabilities such as filtering by criteria, accessing historical data, or managing alerts. This creates significant gaps that will hinder agent workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

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