Skip to main content
Glama
horustechltd

horus-flow-mcp

by horustechltd

get_liquidation_heatmap

Identify liquidation zones with dollar amounts to avoid forced closures of leveraged positions and prevent cascading price moves.

Instructions

Get liquidation zones with dollar amounts — where leveraged positions will be force-closed.

Returns clusters of long and short liquidations at specific price levels
with total dollar amounts. Critical for avoiding entries near massive
liquidation zones that could trigger cascading price moves.

Args:
    symbol: Trading pair (default: ETHUSDT)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoETHUSDT

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler for the 'get_liquidation_heatmap' tool. It is decorated with @mcp.tool(), takes a symbol parameter (default: ETHUSDT), fetches data from the /v1/intelligence/liquidation-heatmap endpoint via the _fetch helper, and returns the JSON result as a string.
    @mcp.tool()
    async def get_liquidation_heatmap(symbol: str = "ETHUSDT") -> str:
        """Get liquidation zones with dollar amounts — where leveraged positions will be force-closed.
        
        Returns clusters of long and short liquidations at specific price levels
        with total dollar amounts. Critical for avoiding entries near massive
        liquidation zones that could trigger cascading price moves.
        
        Args:
            symbol: Trading pair (default: ETHUSDT)
        """
        data = await _fetch(f"/v1/intelligence/liquidation-heatmap?symbol={symbol}")
        return json.dumps(data, indent=2)
  • The docstring serves as the schema/description for this tool. It documents that the tool returns liquidation zones with dollar amounts at specific price levels for leveraged positions.
    """Get liquidation zones with dollar amounts — where leveraged positions will be force-closed.
    
    Returns clusters of long and short liquidations at specific price levels
    with total dollar amounts. Critical for avoiding entries near massive
    liquidation zones that could trigger cascading price moves.
    
    Args:
        symbol: Trading pair (default: ETHUSDT)
    """
  • The tool is registered with MCP via the @mcp.tool() decorator on line 208, which automatically registers it with the FastMCP server instance.
    @mcp.tool()
  • The _fetch helper function that gets called by get_liquidation_heatmap. It makes an HTTP GET request to the RapidAPI endpoint, handles responses (success, 401/403 auth errors, 429 rate limits, and other errors), and returns the parsed JSON dict.
    async def _fetch(endpoint: str) -> dict:
        """Fetch data from the live RapidAPI endpoint."""
        async with httpx.AsyncClient(timeout=10.0) as client:
            try:
                resp = await client.get(
                    f"{RAPIDAPI_BASE_URL}{endpoint}",
                    headers=HEADERS,
                )
                if resp.status_code == 200:
                    return resp.json()
                elif resp.status_code in [401, 403]:
                    return {
                        "error": True,
                        "signal": "UNAUTHORIZED",
                        "detail": "Invalid or missing RAPIDAPI_KEY. Please verify your RapidAPI subscription."
                    }
                elif resp.status_code == 429:
                    return {
                        "error": True,
                        "signal": "RATE_LIMITED",
                        "detail": "You have exceeded your RapidAPI quota. Please upgrade your plan."
                    }
                return {
                    "error": True,
                    "status_code": resp.status_code,
                    "detail": resp.text,
                }
            except Exception as e:
                return {
                    "error": True,
                    "detail": f"Network Error: {str(e)}"
                }
Behavior3/5

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

No annotations are provided, so the description must bear all behavioral disclosure. It explains the tool returns clusters with dollar amounts but doesn't mention read-only behavior or any potential side effects. While it adds value, it could be more transparent about its idempotency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two paragraphs with an args list; the first sentence is clear and direct. However, the second paragraph partly restates the first, and the overall length could be trimmed without losing meaning.

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

Completeness4/5

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

Given the tool has only one parameter and an output schema exists, the description adequately explains the tool's purpose and return structure. It adds context about critical use cases, making it largely complete for an agent.

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?

The input schema has 0% description coverage for the 'symbol' parameter, but the description explicitly states 'symbol: Trading pair (default: ETHUSDT)', which adds meaning beyond the schema's type and default. This compensates for the schema gap.

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 tool retrieves liquidation zones with dollar amounts, specifying that it returns clusters of long and short liquidations at specific price levels. This differentiates it from sibling tools that focus on flows or intelligence, though not explicitly naming alternatives.

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

Usage Guidelines3/5

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

The description implies use for avoiding entries near large liquidation zones to prevent cascading moves, but lacks explicit when-not-to-use or alternative suggestions. It provides a clear use case without situational exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/horustechltd/horus-flow-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server