crypto-liquidations-mcp
This server streams real-time cryptocurrency liquidation data from Binance and provides tools to access and analyze it.
Stream real-time liquidation events from Binance for market analysis
Store up to 1000 recent liquidation events in memory (no persistent storage)
Retrieve liquidations as a Markdown table using the
get_latest_liquidationstool with an optionallimitparameterAnalyze liquidation trends via the
analyze_liquidationstool to examine frequency, volume, and market impact
Streams real-time cryptocurrency liquidation events from Binance's WebSocket API, enabling access to market volatility data including trading pairs, prices, quantities, and buy/sell directions.
Formats liquidation data into Markdown tables with columns for Symbol, Side, Price, Quantity, and Time, making the information more readable and structured.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@crypto-liquidations-mcpshow me the 10 most recent liquidation events"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Crypto Liquidations MCP
An MCP server that streams real-time cryptocurrency liquidation events from Binance, enabling AI agents to react instantly to high-volatility market movements.
Features
Real-time Liquidation Streaming: Connects to Binance WebSocket to capture liquidation events.
Liquidation Data Storage: Maintains an in-memory list of up to 1000 liquidation events, with no persistent storage.
Tool:
get_latest_liquidations:Retrieves the latest liquidation events in a Markdown table.
Columns:
Symbol,Side,Price,Quantity,Time(HH:MM:SS format).Parameters:
limit(default 10).
Prompt:
analyze_liquidations:Generates a prompt to analyze liquidation trends across all symbols, leveraging the
get_latest_liquidationstool.
Related MCP server: binance-alpha-mcp
Prerequisites
Python 3.10: Required for compatibility.
uv: Package and dependency manager (install instructions below).
Internet Access: To connect to Binance WebSocket.
Installation
Installing via Smithery
To install Crypto Liquidations for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @kukapay/crypto-liquidations-mcp --client claude1. Clone the Repository
git clone https://github.com/kukapay/crypto-liquidations-mcp.git
cd crypto-liquidations-mcp2. Install Dependencies
Install required packages using uv:
uv sync3. Integrate with an MCP Client
Configure your MCP client to connect to the server. For Claude Desktop:
{
"mcpServers": {
"crypto-liquidations": {
"command": "uv",
"args": ["--directory", "/path/to/crypto-liquidations-mcp", "run", "main.py"]
}
}
}Usage
To get started, launch the MCP server to begin streaming liquidation events from Binance. The server runs quietly, collecting up to 1000 recent events in memory without generating logs or saving data to disk.
Retrieving Liquidation Events
Use the get_latest_liquidations tool to fetch the most recent liquidation events. You can specify how many events to retrieve (up to 1000) using the limit parameter. For example, you might ask:
"Show me the 5 most recent liquidation events from Binance."
This will return a neatly formatted table showing the trading pair, buy or sell side, price, quantity, and the time of each liquidation in HH:MM:SS format.
Example Output:
| Symbol | Side | Price | Quantity | Time |
|----------|------|--------|----------|----------|
| BTCUSDT | BUY | 50000 | 1.5 | 14:30:45 |
| ETHUSDT | SELL | 3000 | 10.0 | 14:30:40 |
| BNBUSDT | BUY | 500 | 20.0 | 14:30:35 |
| ADAUSDT | SELL | 1.2 | 1000.0 | 14:30:30 |
| XRPUSDT | BUY | 0.8 | 5000.0 | 14:30:25 |This table makes it easy to see recent market activity, such as large buy or sell liquidations on Binance.
Analyzing Liquidation Trends
The analyze_liquidations prompt helps you dive deeper into the data. It generates instructions for analyzing liquidation trends across all trading pairs, focusing on frequency, volume, and market impact. The prompt suggests using the get_latest_liquidations tool to fetch data, ensuring you have the latest information to work with.
This is particularly useful for understanding broader market dynamics, such as whether liquidations are increasing or signaling significant price movements.
License
This project is licensed under the MIT License. See the LICENSE file for details.
Available Tools
1 toolget_latest_liquidationsA
Retrieve the latest liquidation events from Binance in a table format.
Args:
limit (int): The maximum number of liquidation events to return (default: 10, max: 1000).
ctx (Context, optional): The MCP context for logging and server interaction. Defaults to None.
Returns:
str: A Markdown table containing the latest liquidation events, sorted by timestamp in descending order.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ctx | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal that results are sorted by timestamp in descending order and returned as a Markdown table, which are useful behavioral traits. However, it doesn't mention rate limits, authentication requirements, data freshness, error conditions, or whether this is a read-only operation (though 'retrieve' implies it). The description adds some value but leaves significant behavioral aspects unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and front-loaded the core purpose. Every sentence adds value: the first states what the tool does, followed by parameter explanations and return format. It could be slightly more concise by integrating the default values more seamlessly, but overall it's efficient and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description provides good contextual coverage. It explains the tool's purpose, parameters, and return format clearly. The main gap is the lack of behavioral details like rate limits or authentication, but for a data retrieval tool with well-documented parameters, this is reasonably complete. The absence of an output schema is mitigated by the clear return value description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides excellent parameter semantics beyond the input schema. While schema description coverage is 0%, the description clearly explains both parameters: 'limit' with its default (10) and maximum (1000) values, and 'ctx' as optional with its purpose ('MCP context for logging and server interaction'). This fully compensates for the lack of schema descriptions and adds meaningful context about parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('retrieve'), resource ('latest liquidation events from Binance'), and output format ('table format'). It distinguishes itself by specifying the source (Binance) and format (Markdown table), making the purpose unambiguous even without sibling tools for comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. While there are no sibling tools listed, it doesn't mention any prerequisites, constraints, or scenarios where this tool would be appropriate versus other data retrieval methods. The only implicit guidance is the focus on 'latest' events, but no explicit usage context is provided.
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.
1 tool update
- First observed
get_latest_liquidations
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as retrieving liquidation events from Binance, making it distinct by default.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'get_latest_liquidations' follows a clear verb_noun pattern, which would be consistent if more tools were added.
A single tool is too few for a server focused on crypto liquidations, as it severely limits functionality. The scope suggests a need for more operations, such as filtering by asset, time range, or exchange, making this feel incomplete and thin.
The tool surface is significantly incomplete for the domain of crypto liquidations. While it provides a basic retrieval function, there are obvious gaps, such as no ability to filter by parameters like asset type, exchange, or time period, which are essential for practical use.
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