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Three-Little-Birds

XFOIL MCP Server

by Three-Little-Birds
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Python
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Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as computing aerodynamic polars using XFOIL, leaving no room for confusion with other tools.

    Naming Consistency5/5

    The single tool follows a clear verb_noun pattern (compute_polar), and there are no other tools to create inconsistency. The naming is straightforward and descriptive, adhering to a consistent convention.

    Tool Count2/5

    One tool is too few for a server named 'XFOIL MCP Server', which suggests a broader scope for aerodynamic analysis. While the tool covers a core function, the lack of additional tools (e.g., for airfoil geometry manipulation, result visualization, or batch processing) makes the set feel incomplete and limited in utility.

    Completeness2/5

    The tool provides polar computation, but the server likely aims to support aerodynamic workflows. There are significant gaps, such as tools for generating or modifying airfoil coordinates, analyzing specific points, or handling multiple analyses, which limits the server's ability to cover the domain comprehensively.

  • Average 2.9/5 across 1 of 1 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 is passing

  • This repository is licensed under MIT License.

  • 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 carries the full burden of behavioral disclosure. It mentions that the tool 'Returns lift/drag polar tables and solver metadata,' which hints at output but lacks details on performance (e.g., computational cost, error handling, or runtime behavior). For a tool involving complex simulations, this is insufficient to inform safe and effective use.

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

    Conciseness4/5

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

    The description is concise and front-loaded, with two sentences that efficiently cover purpose and output. Every sentence adds value, avoiding redundancy. It could be slightly more structured for clarity but remains appropriately sized for the tool's complexity.

    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's complexity (simulation with multiple parameters) and no annotations, the description is moderately complete but has gaps. It mentions output types, which aligns with the presence of an output schema, but lacks behavioral context and detailed parameter guidance. For a tool with such technical depth, more context would be beneficial.

    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 description adds minimal parameter semantics beyond the schema, mentioning 'airfoil coordinates or NACA code plus sweep parameters' and 'Reynolds angle of attack sweep,' which loosely maps to schema fields. However, with 0% schema description coverage, it doesn't fully compensate by explaining parameter roles, formats, or interactions, leaving gaps in understanding.

    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's purpose: 'Run XFOIL for an airfoil at specified Reynolds angle of attack sweep.' It specifies the verb ('Run XFOIL'), resource ('airfoil'), and scope ('polar sweep'), though it doesn't differentiate from siblings as none exist. The description is specific but could be slightly more precise about the computational nature.

    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?

    The description provides no guidance on when to use this tool versus alternatives, prerequisites, or constraints. It mentions input options ('airfoil coordinates or NACA code') but lacks explicit usage context, such as typical scenarios or limitations, leaving the agent with minimal operational direction.

    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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