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Yahoo Finance MCP Server

Yahoo Finance MCP Server

search_symbols

Read-onlyIdempotent

Resolve a company or brand name to ticker symbols before querying quotes or fundamentals. Returns matching symbols, exchanges, and instrument types so you can choose the correct listing.

Instructions

Resolve a company name or keyword to ticker symbols; each match returns the symbol, name, exchange, and instrument type (equity, ETF, and so on).

Use this first when you have a company or brand name but not its ticker, then pass the resolved symbol to the other tools. Skip it when you already have a valid ticker. Not for fetching prices or fundamentals. A name often matches several listings (the US share, foreign listings, ETFs): choose by exchange and type, not just the first row.

query is the name/keyword to search; count caps the number of matches (1-20, default 8). Returns Markdown by default, or JSON when response_format='json'. No matches returns a short message.

Input Schema

NameRequiredDescriptionDefault
countNoMaximum number of matches to return (1-20)
queryYesCompany name or keyword to search for (e.g., 'Apple', 'electric vehicles', 'Berkshire')
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown

Output Schema

NameRequiredDescriptionDefault
countNo
queryNo
messageNoSet instead of data when there is nothing to return for this request (for example, no dividends on record).
resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.6.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that: a name often returns multiple listings, and empty results return a short message rather than an error. It does not discuss rate limits or result ordering, keeping it short of a 5.

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 purpose, then usage, then caveats, then parameters - a sensible ordering with no wasted preamble. The final sentence largely repeats schema details already available, which is minor redundancy rather than confusion.

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 no explanation, and the description covers the remaining decision points: when to call it, what ambiguity looks like, how to disambiguate, and what empty results look like. Nothing an agent needs in order to call this 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 query, count, and response_format are already documented with bounds, defaults, and enum values. The description restates the same facts ('count caps the number of matches (1-20, default 8)') without adding new semantics, apart from tying query to the multi-listing reality. 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 ('Resolve a company name or keyword to ticker symbols') and enumerates what each match returns (symbol, name, exchange, instrument type). This clearly separates it from the many ticker-consuming siblings like get_stock_quote and get_company_info.

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?

Gives explicit when-to-use ('Use this first when you have a company or brand name but not its ticker'), when-to-skip ('Skip it when you already have a valid ticker'), and an explicit exclusion ('Not for fetching prices or fundamentals'). It also adds disambiguation guidance for the ambiguous case: pick by exchange and type rather than the first row.

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