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vlearner

mcp-etf-holdings

by vlearner

search_etfs

Search ETFs by name, theme, or category to get matching tickers and exchanges for holdings, comparisons, or performance analysis.

Instructions

Search for ETFs by name, theme, or category using Yahoo Finance search.

Returns matching ETF tickers with their full names and exchanges. Useful for discovering ETFs to pass to etf_info, compare_etfs, etf_holdings, or find_etfs_holding_stock.

To resolve a stock or company name rather than find ETFs, use lookup_symbol.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of ETFs to return (1-25, default 10)
queryYesSearch term: fund name, theme, or category, e.g. 'semiconductor' or 'dividend'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A4.3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses the data source and that results include ticker, name, and exchange, but says nothing about rate limits, failure/empty-result behavior, or whether results are cached or live. Adequate context for a simple read search, but not rich.

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?

Three short sentences, zero waste, front-loaded with purpose, then return, then routing. Every sentence earns its place.

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

Completeness5/5

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

An output schema exists, so return values need not be spelled out further, and the description already covers purpose, discovery role, and the sibling alternative. Nothing an agent needs to invoke it correctly is missing.

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?

Schema coverage is 100%, so both parameters are already documented, including the query examples ('semiconductor', 'dividend') that the description echoes. The description adds no syntax or format guidance 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?

States a specific verb and resource ('Search for ETFs') plus the scope of the search (name, theme, or category) and the backing source (Yahoo Finance). It also summarizes the return (matching tickers with names and exchanges), so an agent can distinguish it from siblings like etf_info without opening schemas.

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?

Names the downstream consumers (etf_info, compare_etfs, etf_holdings, find_etfs_holding_stock), which tells the agent this is a discovery entry point. It also gives an explicit when-not with the alternative: use lookup_symbol to resolve a stock or company name instead.

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