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horustechltd

horus-flow-mcp

by horustechltd

get_market_intelligence

Retrieve a unified market intelligence report including orderflow signal, composite score, liquidation zones, cross-exchange analysis, climate, and ignition state. Ideal for comprehensive pre-trade checks.

Instructions

Get complete market intelligence in a single call — combines all endpoints.

Returns orderflow signal, composite score, liquidation zones, cross-exchange
analysis, climate, and ignition state in one unified response. Use this
for a comprehensive pre-trade check.

Args:
    symbol: Trading pair (default: BTCUSDT)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoBTCUSDT

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function that executes the tool 'get_market_intelligence'. It is an async function decorated with @mcp.tool(), takes a symbol parameter (default 'BTCUSDT'), fetches data from the '/v1/intelligence/market-intelligence?symbol={symbol}' endpoint via the _fetch helper, and returns the JSON result as a string.
    async def get_market_intelligence(symbol: str = "BTCUSDT") -> str:
        """Get complete market intelligence in a single call — combines all endpoints.
        
        Returns orderflow signal, composite score, liquidation zones, cross-exchange
        analysis, climate, and ignition state in one unified response. Use this
        for a comprehensive pre-trade check.
        
        Args:
            symbol: Trading pair (default: BTCUSDT)
        """
        data = await _fetch(f"/v1/intelligence/market-intelligence?symbol={symbol}")
        return json.dumps(data, indent=2)
  • The tool is registered via the @mcp.tool() decorator at line 266, which registers 'get_market_intelligence' as an MCP tool on the FastMCP server instance.
    @mcp.tool()
    async def get_market_intelligence(symbol: str = "BTCUSDT") -> str:
  • The _fetch helper function used by get_market_intelligence to make HTTP requests to the RapidAPI endpoint. Handles authentication, rate limiting, and network errors.
    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)}"
                }
  • Input parameter definition: symbol (string, default 'BTCUSDT') with docstring description.
    Args:
        symbol: Trading pair (default: BTCUSDT)
    """
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits itself. It explains what data is returned but does not mention any limitations, auth needs, rate limits, or data freshness. This is insufficient for a tool combining multiple endpoints.

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

Conciseness4/5

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

The description is mostly concise with two clear introductory sentences and a parameter doc. The Args section could be integrated more smoothly, but overall it's well-structured.

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 complexity (combining multiple analyses) and the presence of an output schema, the description adequately explains the return contents and parameter. It lacks mention of any usage restrictions or error handling, but otherwise is fairly complete.

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 description adds meaning to the symbol parameter beyond the schema: 'Trading pair (default: BTCUSDT)'. Since schema coverage is 0%, this extra context is valuable, though it could specify format or constraints.

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

Purpose5/5

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

The description clearly states it returns a combination of multiple endpoints (orderflow signal, composite score, etc.), distinguishing it from sibling tools that likely return individual metrics. The verb 'Get' with 'complete market intelligence' is specific.

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 advises using this for a comprehensive pre-trade check, giving a clear context. However, it does not explicitly state when not to use it (e.g., if only one component is needed) or mention alternative sibling tools for specific data.

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

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