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Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'think' has a clearly defined and distinct purpose for reasoning without external actions.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The name 'think' is straightforward and follows a simple verb pattern.

    Tool Count2/5

    One tool is too few for most server purposes, as it severely limits functionality and scope. This feels thin and incomplete, even for a specialized server like 'MCP Think Tool Server', which might benefit from additional reasoning or analysis tools.

    Completeness1/5

    The server is severely incomplete; a single 'think' tool does not provide a coherent surface for any meaningful domain. There are significant gaps, as it lacks any tools for input, output, or interaction beyond internal reasoning, making it impractical for most agent workflows.

  • Average 3.7/5 across 1 of 1 tools scored.

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

    • 1 of 1 community issues answered or closed 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 failing
  • 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

  • Behavior4/5

    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 clearly states 'It will not obtain new information or change anything', which effectively communicates read-only, non-destructive behavior. It also implies the tool is for internal reasoning processes. While it doesn't cover rate limits or detailed operational constraints, it provides sufficient behavioral context for a tool with no annotations.

    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 appropriately sized with two main sentences followed by parameter documentation. The first sentence states the purpose, the second provides usage guidance, and the Args section adds necessary parameter context. There's minimal waste, though the formatting with indentation could be slightly cleaner.

    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 conceptual nature (thinking/analysis), no output schema, and no annotations, the description provides adequate context about what the tool does and when to use it. However, it doesn't explain what the tool actually produces (e.g., structured output, internal state change) or how the 'thinking' manifests operationally, leaving some gaps in completeness.

    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 schema description coverage is 0%, so the description must compensate. It provides a detailed explanation of the 'thought' parameter, describing it as 'structured reasoning, step-by-step analysis, policy verification, or any other mental process that helps with problem-solving'. This adds substantial meaning beyond the bare schema, though it doesn't specify format constraints or examples.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose3/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description states the tool is for 'thinking about something' and mentions 'complex reasoning', which provides a general purpose. However, it's vague about what 'thinking' entails operationally and doesn't distinguish from siblings (though none exist). It avoids tautology by adding context about reasoning, but lacks specificity about the verb+resource combination.

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

    Usage Guidelines4/5

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

    The description explicitly states 'Use it when complex reasoning is needed', providing clear context for when to invoke the tool. It also mentions 'It will not obtain new information or change anything', which helps exclude alternative use cases. However, with no sibling tools, there's no need for differentiation, so it can't score a 5 for explicit alternatives.

    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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  • Evaluate tool definition quality.

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