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mikeysrecipes

Coinmarket MCP Server

by mikeysrecipes
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Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation2/5

    The two tools both retrieve cryptocurrency market data, and the vague descriptions make it unclear whether get_quotes is for individual coins or a different listing format. Agents may struggle to choose between them for a given request.

    Naming Consistency5/5

    Both tools follow a consistent get_<object> pattern with clear verb-noun structure. The naming is predictable and easy to understand.

    Tool Count3/5

    With only 2 tools, the server feels minimal but not entirely insufficient for basic market data retrieval. The scope is limited, but the count is borderline, not extreme.

    Completeness2/5

    The server lacks obvious capabilities such as historical data, currency conversion, or detailed metadata lookups, making it incomplete for a comprehensive cryptocurrency market server. Only the most basic listing and quote operations are covered.

  • Average 2.9/5 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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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

  • Behavior2/5

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

    With no annotations, the description carries the full burden of behavioral disclosure. 'Get' implies a read-only operation, but the description does not explain what 'quotes' entails (e.g., current price, historical data), whether any limitations exist, or what the response contains. This is minimal and relies on inference.

    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 and front-loaded, but it is under-specified. It does not earn its place beyond restating the tool's name, as it conveys almost no additional value.

    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 the lack of annotations, output schema, and parameter descriptions, the description is far from complete. It does not clarify what the quotes are, how the parameters work, or what the expected return values are, leaving the agent with insufficient context to use the tool correctly.

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

    Parameters1/5

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

    The schema provides only parameter names and types (slug, symbol) with no descriptions, and schema description coverage is 0%. The description adds no information about what these parameters mean or how they affect the request, so the agent has no guidance on how to populate them.

    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 states a specific verb and resource: 'Get cryptocurrency quotes' clearly indicates the tool retrieves quote data. It distinguishes from the sibling 'get_currency_listings' by focusing on quotes rather than listings, though it does not explicitly name the sibling.

    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 the sibling 'get_currency_listings'. There is no mention of context, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.

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

  • Behavior3/5

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

    With no annotations, the description carries the full burden of behavioral disclosure. 'Get' implies a read-only operation and 'latest' suggests current data, but there are no details about response format, ordering, or limitations. It is adequate but minimal.

    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?

    The description is a single concise sentence, front-loaded with the core action. It contains no fluff or unnecessary words, making it efficient for an agent to parse.

    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?

    Given the tool has no parameters and no output schema, the description is minimally adequate for understanding the operation. However, it lacks an explicit statement of what the returned listings contain, which could lead to ambiguity for an agent.

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

    Parameters4/5

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

    The tool has zero parameters, so the schema is fully complete and requires no additional description. The baseline of 4 applies since there are no parameters to elaborate on.

    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 'Get latest cryptocurrency listings' uses a specific verb (Get), a clear resource (cryptocurrency listings), and a scope (latest). This makes the core purpose understandable, although it does not explicitly distinguish it from the sibling tool get_quotes.

    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 usage guidance is provided. The description does not mention when to use this tool versus get_quotes or any alternatives, leaving the agent without explicit context for tool selection.

    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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