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ApexVol MCP Server

ApexVol MCP Server

by ryansilk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Smart Money Flow

get_smart_money_flow
Read-only

Identify institutional options trades by filtering for large orders, sweeps, and block trades to reveal smart money flow.

Instructions

Identify institutional/smart money options trades.

Filters for large trades, sweeps, and block orders that may indicate informed positioning.

Use this tool when the user asks about:

  • Smart money or institutional flow

  • Large options trades

  • Block trades or sweeps

  • Whale activity

Args: ticker: Stock symbol

Returns: Smart money flow patterns and significant trades

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ticker": "<ticker>"
    },
    "name": "get_smart_money_flow"
  }
}

Input Schema

NameRequiredDescriptionDefault
tickerYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4/5.0
Behavior3/5

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

The readOnlyHint is already annotated, so the description adds modest filtering behavior: what criteria are important (large trades, sweeps, blocks) and that returns are 'patterns and significant institutional labels'. The high-level return shape is mentioned but details like output structure, pagination, and lookback window are absent.

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 compact, front-loaded with the capability, and uses clear sections for usage triggers, arguments, and returns. Every sentence contributes; there is no filler.

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?

For a one-parameter, read-only tool with no output schema, this supplies the key behavioral context, explicit user-intent triggers, and a high-level returned value. It would be fully complete if it also detailed the exact output structure or explained how it differs from the sibling get_options_flow tool.

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

Parameters3/5

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

The description says 'ticker: Stock symbol', which is a small advance beyond the schema's bare 'Ticker' title. For a single self-evident parameter, this meets the minimum viable compensation for schema-less parameter descriptions, but adds little new meaning.

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 purpose is crisp and specific: 'Identify institutional/smart money options trades' through large trades, sweeps, and block orders. This clearly differentiates it from more generic flow or analytics tools like get_options_ flow.

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

Usage Guidelines4/5

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

The description gives an explicit bulleted list of when to use it: smart money/institutional flow, large trades, blocks, sweeps, and wholes. It does not name analogous alternatives or 'when not to use', so it just misses the top score.

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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