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lkcair

yfinance-ai MCP server

by lkcair

search_ticker

Read-onlyIdempotent

Find ticker symbols by company name or keyword. Use this to look up the stock identifier you need before fetching quotes or financial data.

Instructions

Search for ticker symbols by company name or keyword.

Args: query: Company name or keyword to search

Returns: List of matching tickers

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds no behavioral context beyond that — it doesn't explain match semantics (prefix vs fuzzy), result ordering, or the open-world nature of querying an external source. It only restates that a list is returned, which the output schema already covers.

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?

Front-loaded with the purpose, then a compact Args/Returns block. Efficient and scannable. The Returns section is mildly redundant given an output schema exists, but the whole entry is short and waste-free.

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

Completeness3/5

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

For a single-parameter read-only search with an output schema and full annotations, this is adequate — return values needn't be explained. The gap is the absence of any disambiguation from validate_ticker/get_trending_tickers and no guidance for ambiguous queries, which matters in a 70+ sibling toolset.

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 description coverage is 0% — the only property is titled 'Query' with no description. The description partially compensates by defining it as 'Company name or keyword to search', which is more informative than the bare schema title. It does not, however, give format examples (e.g., 'Apple' vs 'AAPL') or note case/matching behavior.

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?

States a specific verb and resource: search ticker symbols by company name or keyword. An agent immediately understands the operation. However, it does nothing to distinguish itself from siblings like validate_ticker or get_trending_tickers, which also involve ticker resolution.

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?

Usage is only implied — the phrase 'by company name or keyword' suggests it is for resolving a symbol you don't yet know. There is no explicit when-to-use statement, no mention of validate_ticker as the alternative for confirming a known symbol, and no guidance on ambiguous or multi-match results.

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