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Pantainos-Toolkit

grok-mcp

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusing it with another. The tool's purpose is clearly distinct by default.

    Naming Consistency5/5

    The tool name 'search_x' follows a clear verb_noun pattern and is a single, coherent naming choice. No inconsistency exists with only one tool.

    Tool Count3/5

    A single tool is borderline for a server named 'grok-mcp'. While the narrow search-and-summarize scope justifies a single tool, the surface feels thin and could benefit from additional related tools.

    Completeness4/5

    The tool covers the core search-and-summarize function well, but lacks complementary operations like retrieving raw posts, user timelines, or trending topics. Minor gaps agents can work around, but not a dead end.

  • Average 4/5 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 status not available
  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

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  • 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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      "maintainers": [
        "your-github-username"
      ]
    }

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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?

    The description adds valuable behavioral context beyond the readOnlyHint and openWorldHint annotations: it discloses that the tool operates autonomously, searches, analyzes, and synthesizes answers grounded in real posts, and includes citations. This informs the agent about the tool's internal behavior, though it does not disclose potential limitations like rate limits or authentication requirements.

    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 compact—two sentences—and front-loads the core purpose. Every sentence adds meaningful information: the first states the main function, the second explains the autonomous synthetic process. No unnecessary filler or repetition.

    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?

    With an output schema available, the description does not need to explain return values, and it already covers the essential purpose, process, and output type ('summarised answer with citations'). It could include more on limitations or prerequisites, but for a search tool with rich schema and annotations, it is adequately complete.

    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 already provides 100% coverage with detailed descriptions for all 8 parameters (e.g., query, date filters, temperature, allowed/excluded handles). The tool description itself does not add parameter-level information, so it stays at the baseline 3 without adding or requiring compensation.

    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 a specific action ('Search X (Twitter) posts') and the resource (X posts) using Grok, with a distinct outcome ('return a summarised answer with citations'). It also explains the autonomous process, making the tool's purpose unmistakable even in the absence of sibling tools.

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

    Usage Guidelines3/5

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

    The description implies usage for querying X posts and receiving a synthesized answer, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. With no sibling tools, the lack is less critical, but the absence of exclusions or context (e.g., 'use for real-time social media analysis') keeps this at a mid score.

    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 the MCP server is working as expected.
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  • Evaluate tool definition quality.

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