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mcp-etf-holdings

by vlearner

etf_info

Fetch metadata for a single ETF: name, category, AUM, expense ratio, NAV, and trailing returns. For multiple ETFs, use compare_etfs instead.

Instructions

Return metadata for a single ETF: name, category, AUM, expense ratio, NAV, and trailing returns.

For two or more ETFs, use compare_etfs instead — it returns one table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesETF ticker symbol, e.g. 'SPY' or 'QQQ'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden. It implies a pure read operation and lists what comes back, but never states read-only status, auth requirements, rate limits, or behavior for an unknown ticker. Adequate for a trivial one-param lookup, but thin for a tool with zero annotation coverage.

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?

Two tight sentences with the primary purpose front-loaded and the routing rule appended. Minor waste: enumerating the returned fields duplicates what the output schema already declares.

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?

With one required, fully documented parameter and a companion output schema, the description supplies everything needed to select and call the tool correctly. Only the absence of any error/permission context keeps it short of a 5.

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?

Only one parameter (ticker) and schema coverage is 100%, with the schema already supplying the 'SPY'/'QQQ' example. The description adds nothing beyond the schema, so the baseline 3 applies.

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?

Specific verb ('Return') plus resource ('metadata for a single ETF') and an explicit enumeration of the returned fields (name, category, AUM, expense ratio, NAV, trailing returns). It is immediately distinguishable from the sibling compare_etfs, which is named directly.

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

Usage Guidelines5/5

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

The second sentence gives an explicit when-not rule: for two or more ETFs, use compare_etfs instead, with the rationale (it returns one table). This is a clear alternative routing rule rather than implied usage.

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