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tharunn2007

NitroStack Calculator MCP Server

by tharunn2007
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TypeScript

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool addresses a distinct function: arithmetic calculation and temperature conversion. There is no overlap or ambiguity between the two tools.

    Naming Consistency4/5

    Both tools use imperative verb forms, but 'calculate' is a bare verb while 'convert_temperature' includes an object. This is a minor stylistic inconsistency, yet the names are predictable and readable.

    Tool Count3/5

    With only two tools, the server is minimal but covers its narrow purpose. The count falls at the low end of the acceptable range, feeling slightly thin for a general-purpose calculator.

    Completeness4/5

    The server covers basic arithmetic and temperature conversion between Celsius and Fahrenheit. The lack of Kelvin support is a minor gap, but the core calculator functionality is complete.

  • Average 3.2/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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

  • Behavior2/5

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

    With no annotations provided, the description must disclose behavioral traits. It only says 'perform basic arithmetic calculations,' which is a tautological high-level statement. It doesn't mention return format, error handling (e.g., division by zero), or any side effects. This leaves the agent without crucial information.

    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 short sentence that immediately states the tool's purpose. No filler or redundancy; every word earns its place.

    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?

    The tool is simple, but the description lacks any mention of the return value or edge cases, and there is no output schema. The schema covers parameters fully, but the description's one-liner is minimally adequate without being complete for an agent to fully predict tool behavior.

    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?

    The input schema has 100% parameter description coverage, documenting a, b, and operation with clear enums. The description adds no additional parameter meaning, so the baseline 3 applies.

    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 the tool performs basic arithmetic calculations, which is a clear verb+resource. It doesn't list specific operations, leaving that to the schema, and it doesn't explicitly differentiate from the sibling convert_temperature, but the resource 'arithmetic' is distinct enough.

    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 convert_temperature or any alternative. The description only states what it does, not when it should be selected.

    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?

    With no annotations, the description carries the full burden of behavioral disclosure. It lacks key details such as the fact that file parameters are always required (contradicting the 'direct input' suggestion), and it does not clarify what happens if both 'value' and 'file_content' are supplied. No return behavior or side effects are disclosed.

    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 only two sentences long, front-loaded with the primary action and scope. It is concise and every word contributes meaning, though it could profitably include a bit more detail without losing compactness.

    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?

    Despite a simple temperature conversion purpose, the tool has six parameters and three required file-related fields. The description does not explain the relationship between file content and direct input, nor does it mention the mandatory file parameters. This creates a critical gap for correct invocation, especially with no output schema.

    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 100%, so the input schema already documents all six parameters. The description adds minimal semantic value—merely restating that C and F are supported—which aligns with the baseline of 3 for complete schema coverage.

    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?

    The description clearly identifies a specific verb ('Convert') and resource ('temperature units'), distinguishing it from the sibling 'calculate' tool. It also names the supported scales (Celsius and Fahrenheit), leaving no doubt about the tool's core function.

    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 for when to use this tool versus the sibling 'calculate'. The phrase 'based on file content or direct input' hints at usage contexts, but there are no explicit criteria or exclusions, leaving the agent to infer when conversion is appropriate.

    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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