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Otman404

yfinance MCP Server

by Otman404
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    get_news and get_price target distinct aspects (news vs. price) with no overlap. An agent can easily choose the correct tool for the intended action.

    Naming Consistency5/5

    Both tools follow the consistent pattern of get_<resource>, using snake_case and a clear verb-noun structure. No deviations.

    Tool Count2/5

    With only 2 tools for a domain as rich as stock/crypto data, the set is far too sparse. Most financial APIs offer dozens of endpoints; this limited set feels incomplete.

    Completeness1/5

    Crucial operations are missing: no historical price data, no financial statements, no market statistics, no search. An agent cannot perform basic financial analysis with just news and current price.

  • Average 2.5/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior1/5

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

    No annotations are provided, and the description does not disclose behavioral traits such as network calls, rate limits, authentication needs, or what the 'period' parameter means. The description implies a single price, but the 'period' parameter suggests historical data, creating ambiguity and contradiction.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single sentence, concise but too brief for a tool with untrivial input parameters. It lacks structure and does not front-load critical information beyond the basic purpose.

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

    Completeness2/5

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

    Given no output schema and unannotated parameters, the description does not explain what the tool returns (e.g., a number or object) or how the period affects the output. The context is incomplete for effective use, especially with the ambiguous period parameter.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 2 parameters (ticker, period) with 0% description coverage. The description does not explain the parameters or their expected values (e.g., what '1d' means or other valid periods), adding no value beyond the schema. The agent must infer usage from parameter names alone.

    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?

    The description clearly states the tool gets the price of a stock/crypto ticker, with a specific verb and resource. It distinguishes itself from the sibling 'get_news' by the type of data returned. However, it does not clarify whether it returns current or historical prices, leaving some ambiguity.

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

    Usage Guidelines2/5

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

    There is no guidance on when to use this tool versus alternatives, nor any mention of limitations, prerequisites, or when not to use it. The only sibling is 'get_news', but no explicit comparison is made.

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

  • Behavior2/5

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

    No annotations are provided, so the description must fully disclose behavior. It only states the basic function without mentioning rate limits, data sources, or potential errors. Minimal transparency.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single sentence, which is concise but lacks necessary detail. It is appropriately front-loaded but does not earn its place with substantive information.

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

    Completeness2/5

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

    Given no output schema, the description should hint at return format or data structure. It does not, leaving the agent uninformed about what to expect after invocation.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description adds no additional meaning beyond the input schema. With 0% schema description coverage, it fails to explain what 'ticker' format is expected or what 'count' represents.

    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?

    The description clearly states the tool retrieves news for a stock/crypto ticker, using a specific verb and resource. It distinguishes from the sibling 'get_price' tool which presumably fetches price data.

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

    Usage Guidelines2/5

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

    No guidance is provided on when to use this tool versus 'get_price' or other alternatives. The description lacks any contextual cues for appropriate usage.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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