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edwardpwtsoi

MathJS Calculator MCP Server

by edwardpwtsoi
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JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.4

  • Disambiguation5/5

    The two tools, calculate and derivative, have completely distinct purposes: evaluating an expression versus differentiating it. There is no overlap or ambiguity between them.

    Naming Consistency4/5

    Both tool names are single words, but 'calculate' is a verb while 'derivative' is a noun. A more consistent pattern might use 'differentiate' instead of 'derivative,' but the naming is still clear and predictable.

    Tool Count3/5

    With only 2 tools, the server is very minimal. For a simple calculator this could be acceptable, but it feels thin compared to the typical 3-15 tool range, leaving the server on the borderline.

    Completeness2/5

    The server covers evaluation and differentiation but misses other common mathematical operations like simplification, solving equations, integration, or expansion. This is a significant gap for a calculator-oriented server.

  • Average 3.1/5 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    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 provided, the description carries the full burden. It only states that the tool evaluates an expression, but does not disclose potential side effects, error handling, supported operations, or return value. This is minimal and lacks transparency for an agent.

    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, clear sentence with no wasted words. It is appropriately sized and front-loaded, making it easy to read and understand.

    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?

    The tool is simple, but the description does not provide essential context such as what kinds of expressions are supported, an example, or the output format. Given the absence of an output schema and annotations, the description is incomplete for an agent to use it effectively.

    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 schema provides only the parameter name 'expression' with type string, and the description does not elaborate on how the expression should be formatted or what syntax is expected. With 0% schema coverage, the description fails to compensate by explaining the parameter's format or constraints.

    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 uses a specific verb 'evaluate' and identifies the resource as 'a mathematical expression', clearly stating the tool's function. However, it does not differentiate from the sibling tool 'derivative', which also handles mathematical expressions, so it is clear but lacks sibling distinction.

    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 the sibling 'derivative' or any other alternative. The description simply states what it does, leaving the agent without context for selecting this tool over others.

    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 disclose behavioral traits. It only states the basic calculation and does not mention side effects, input format expectations, output structure, or edge-case behavior. For a pure computational tool, this is a minimal but not transparent description.

    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?

    A single concise sentence that immediately states the action and subject, with no extraneous words. It is front-loaded with the verb and is highly efficient.

    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?

    With no output schema, the description does not explain what the tool returns (e.g., the derivative expression). It also lacks usage guidance and edge-case handling, making it insufficient for a complete understanding of the tool's behavior.

    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 description clarifies the role of 'variable' as the differentiation variable and 'expression' as the operand, adding meaning beyond the bare schema property names, which carry no descriptions. It helps the agent understand how the two parameters relate.

    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 uses the specific verb 'Calculate' and identifies the resource as 'the derivative of an expression with respect to a variable', which clearly differentiates it from the generic sibling 'calculate'. It concisely states exactly what the tool does.

    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 about when to use this tool versus the sibling 'calculate'. There is no mention of exclusions, prerequisites, or contexts where differentiation is appropriate, leaving the agent to infer 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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