MCP server for Yahoo Finance data including stock quotes, historical prices, company financials, and market news for AI agents.
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Average 4.2/5 across 3 of 3 tools scored.
Tools are mostly distinct: single quote, multiple quotes, and comparison. However, get_multiple_quotes and compare_stocks both handle multiple stocks, leading to slight overlap, but descriptions clarify different use cases.
All tools follow a consistent verb_noun snake_case pattern (get_stock_quote, get_multiple_quotes, compare_stocks), with no deviations.
Three tools is appropriate for a stock quote server covering single, multiple, and comparison queries; neither too few nor too many.
Core real-time quoting needs are covered (single, multiple, comparison). Minor gaps like historical data or symbol search exist but are not essential for the primary purpose.
compare_stocksACompare multiple stock securities side-by-side with key financial metrics and performance data. Returns price, P/E ratio, dividend yield, market cap, earnings, revenue, and relative performance for comparison. Use for investment analysis, selecting between stocks, or portfolio optimization.
| Name | Required | Description | Default |
|---|---|---|---|
| tickers | Yes | List of tickers to compare (minimum 2 for meaningful comparison) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true and openWorldHint: true. The description adds specific metrics returned (price, P/E ratio, etc.) but does not disclose additional behavioral traits like data freshness or rate limits. It adds moderate context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with all critical information front-loaded. First sentence states purpose and output, second gives use cases. No redundant or unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 parameter, no output schema), the description adequately explains return values (price, P/E ratio, etc.) and use cases, making it complete for an agent to understand and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'tickers'. The description adds the note 'minimum 2 for meaningful comparison', which provides helpful guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'compare', the resource 'multiple stock securities', and the output 'key financial metrics and performance data'. It distinguishes from siblings by emphasizing side-by-side comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear use cases like 'investment analysis, selecting between stocks, or portfolio optimization' but does not explicitly contrast with siblings or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_multiple_quotesAFetch current stock quotes for multiple ticker symbols in one request. Returns price, change, volume, and key metrics for each stock. Use for portfolio monitoring, screening multiple stocks, or comparing multiple securities at once.
| Name | Required | Description | Default |
|---|---|---|---|
| tickers | Yes | List of stock ticker symbols to retrieve quotes for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint and openWorldHint. The description adds value by specifying the return fields (price, change, volume, key metrics) beyond what annotations provide. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no unnecessary information. Every sentence is informative and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description adequately covers the return fields (price, change, volume, key metrics). For a read-only tool with one parameter, this is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (sole parameter 'tickers' is fully described). The description does not add additional parameter details beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches current stock quotes for multiple ticker symbols and lists return fields (price, change, volume, key metrics). However, it does not differentiate from sibling tools like compare_stocks or get_stock_quote.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for portfolio monitoring and screening multiple stocks, but does not explicitly state when to use this tool versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_stock_quoteAFetch the current stock market quote for an individual ticker symbol. Returns real-time price, intraday change (dollars and percentage), trading volume, market capitalization, P/E ratio, earnings per share, dividend yield, and 52-week high/low. Use for real-time price monitoring, investment decisions, or financial dashboards.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Stock ticker symbol in uppercase (e.g. 'AAPL', 'MSFT', 'NVDA', 'TSLA') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description discloses real-time data and lists returned fields (e.g., intraday change, volume, PE). Consistent with annotations (readOnlyHint, openWorldHint). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences covering purpose, output, and usage. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simple tool with one parameter and no output schema, description sufficiently covers return content and use context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; description adds example formats (uppercase) but doesn't provide meaning beyond schema. Baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'fetch' and resource 'stock market quote for an individual ticker symbol'. Clearly distinguishes from siblings 'compare_stocks' and 'get_multiple_quotes'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states use cases: 'real-time price monitoring, investment decisions, or financial dashboards'. Lacks when-not-to-use guidance relative to siblings.
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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{
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