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vdesabou

MCP Playground Server

by vdesabou

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 has a clearly distinct purpose: help provides detailed information, suggest offers completions, and validate checks correctness with corrections. There is no overlap in functionality, making it easy for an agent to select the right tool.

    Naming Consistency5/5

    All tool names follow a consistent 'playground_command_' prefix with a descriptive suffix (help, suggest, validate), using snake_case uniformly. This pattern is predictable and enhances readability.

    Tool Count5/5

    With 3 tools, the server is well-scoped for its purpose of assisting with playground commands. Each tool serves a specific role (help, suggestion, validation), and there are no unnecessary or missing tools for this focused domain.

    Completeness5/5

    The tool set provides complete coverage for the domain of playground command assistance: help for understanding, suggestions for building commands, and validation for correctness. There are no obvious gaps, and agents can handle typical workflows without dead ends.

  • Average 3/5 across 3 of 3 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 failing
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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 states the tool validates and suggests corrections, but doesn't describe what validation entails (e.g., syntax checks, semantic analysis), how suggestions are formatted, whether it's read-only or has side effects, or any error handling. This leaves significant gaps for a tool that likely involves complex processing.

    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, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core purpose ('Validate a complete playground command') and adds value with the secondary action ('and suggest corrections'). Every part of the sentence earns its place.

    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?

    For a tool with no annotations, no output schema, and likely complex validation logic, the description is insufficient. It doesn't explain what constitutes a 'complete' command, what types of corrections are suggested, or the format of the response. The agent lacks critical context to use this tool effectively beyond the basic parameter.

    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% description coverage, with the 'command' parameter documented as 'Complete playground command to validate.' The description doesn't add any additional meaning beyond this, such as examples of valid commands or formatting requirements. Given the high schema coverage, a baseline score of 3 is appropriate.

    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: 'Validate a complete playground command and suggest corrections.' It specifies the verb ('validate') and resource ('playground command'), and indicates it provides suggestions. However, it doesn't explicitly differentiate from sibling tools like 'playground_command_help' or 'playground_command_suggest'.

    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 its siblings ('playground_command_help' and 'playground_command_suggest'). It doesn't mention prerequisites, alternatives, or exclusions, leaving the agent to infer usage from the tool name alone.

    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 provided, the description carries full burden for behavioral disclosure. While 'Get detailed help' implies a read-only operation, it doesn't specify whether this requires authentication, has rate limits, returns structured or unstructured data, or has any side effects. The description is too minimal for a mutation-free tool with zero annotation coverage.

    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, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for a simple tool and front-loads the essential information.

    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?

    For a simple read-only tool with one well-documented parameter and no output schema, the description is minimally adequate but lacks important context. It doesn't explain what format the help returns (text, structured data), whether it covers all commands, or how it relates to sibling tools. The absence of annotations increases the need for more complete behavioral disclosure.

    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 schema already fully documents the single 'command' parameter. The description doesn't add any additional meaning about parameter usage beyond what's in the schema (e.g., examples of valid commands beyond those shown). Baseline 3 is appropriate when schema does the heavy lifting.

    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 with a specific verb ('Get') and resource ('detailed help for playground commands'), making it immediately understandable. However, it doesn't explicitly differentiate this from its sibling tools (playground_command_suggest and playground_command_validate), which would be needed for a perfect score.

    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 its siblings (suggest and validate) or any alternative approaches. It simply states what the tool does without context about appropriate usage scenarios or exclusions.

    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 provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe how it behaves: no information about response format, error handling, rate limits, authentication needs, or whether it's read-only or mutative. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational characteristics.

    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, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a simple tool and front-loads the essential information. Every word earns its place in this concise formulation.

    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 moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but doesn't provide enough context about when to use it versus siblings, what the response looks like, or behavioral characteristics. Without annotations or output schema, the description should do more to compensate, but it only meets the minimum viable threshold.

    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 schema already documents both parameters thoroughly. The description doesn't add any additional meaning about parameters beyond what's in the schema. It mentions 'partial playground command to complete' which aligns with the schema but provides no extra context about format, examples, or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

    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: 'Get command suggestions and completions for the Kafka Docker Playground CLI'. It specifies the verb ('Get'), resource ('command suggestions and completions'), and target system ('Kafka Docker Playground CLI'). However, it doesn't explicitly differentiate from its siblings (playground_command_help, playground_command_validate), which would be needed for a perfect score.

    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 its siblings (playground_command_help, playground_command_validate). It doesn't mention prerequisites, alternatives, or exclusions. The only implied usage is when you have a partial command to complete, but this is insufficient for effective 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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