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PKWadsy

grok-mcp

by PKWadsy
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.4.0

  • Disambiguation5/5

    ask_grok and check_files serve clearly distinct purposes: one is for querying Grok, the other is a dry-run validator for file resolution. No overlap or ambiguity.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern (ask_grok, check_files), using underscores and clear verbs.

    Tool Count3/5

    Only 2 tools feels thin for a server that provides access to Grok, which could benefit from additional tools for conversation management or specialized searches.

    Completeness2/5

    The tool set lacks basic conversational features like retrieving history or managing context, and the promised web_search/x_search capabilities are not exposed as separate tools, limiting functionality.

  • Average 4.7/5 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.

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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?

    No annotations are provided, so the description carries full burden. It discloses the tool is a dry-run (non-destructive), verifies file resolution, checks context size, and states that file paths resolve relative to /app. It doesn't detail error behavior or rate limits, but for a simple check tool this is adequate.

    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 extremely concise at three sentences, with the primary purpose front-loaded. Every sentence adds essential information without redundancy.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's simplicity, no output schema, and a single sibling, the description covers the core functionality and relationship well. It explains validation equivalence and file resolution. It does not describe the return format, but the overall completeness is sufficient for an agent to use the tool correctly.

    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% coverage with detailed descriptions for all three parameters. The description adds an important context note about file paths resolving relative to /app, which is not in the schema. However, this is environmental context rather than parameter semantics, so the baseline 3 is appropriate.

    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 states the tool performs a 'dry-run file resolution' and explicitly differentiates it from its sibling 'ask_grok' by positioning it as a preparatory verification step. The verb 'check' and noun 'files' are specific.

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

    Usage Guidelines5/5

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

    The description provides explicit usage guidance: 'Use this before ask_grok' and explains that if check_files passes, ask_grok will too. It also notes the same validation logic, giving clear context for when to use this tool versus the alternative.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior5/5

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

    Despite no annotations, the description fully discloses behavioral traits: Grok has no context about conversation or codebase, responses include a response_id for continuation, file inclusion syntax, model options, and search defaults. The limitation of previous_response_id in multi-agent mode is also noted.

    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 fairly long but well-organized, using bold for emphasis and clear sections. Every sentence contributes essential information. Could be slightly more concise, but overall efficient for the complexity covered.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a tool with 9 parameters and no output schema, the description is comprehensive: covers all input aspects, explains the output (response_id), gives continuation guidance, and addresses the critical context limitation. Complete and actionable.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%, but the description adds substantial value: explains the rationale for using files, provides detailed file path syntax, clarifies the purpose of previous_response_id, and describes model options and search behavior. It enriches the parameter meanings significantly beyond the schema.

    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 states 'Ask Grok a question' and outlines what Grok excels at (thinking, planning, architecture, real-time search). It distinguishes from related tools like web_search and x_search, though they are not listed as siblings on this server. The purpose is specific and unambiguous.

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

    Usage Guidelines5/5

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

    Explicitly provides when to use this tool vs alternatives: 'Use web_search for current information... Use x_search to find and analyze posts.' Also gives critical usage guidance: include full context, use files parameter, how to continue conversations with previous_response_id. No ambiguity.

    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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