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witqq

Clipboard MCP Server

by witqq
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JavaScript
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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 single tool 'copy_paste' has a clear, distinct purpose described as copying and pasting content between files using text patterns.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'copy_paste' follows a clear verb-based pattern (copy and paste), and there are no other tools to compare it against for inconsistency.

    Tool Count2/5

    A single tool is generally too few for a server's purpose, as it limits functionality and may indicate an incomplete or overly narrow scope. For a clipboard server, one might expect additional tools like 'cut', 'clear', or operations on different data types, making this count insufficient for robust coverage.

    Completeness2/5

    The server's domain appears to be clipboard operations, but with only one tool for copy/paste, there are significant gaps. Missing operations likely include cutting, clearing, or handling clipboard history, which are common in clipboard functionality, leading to an incomplete surface that could cause agent failures.

  • 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 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

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden. It mentions 'copy/paste' and 'cut' in parameters, implying file modification, but doesn't disclose critical behaviors like whether it creates backups, handles errors, requires file permissions, or has side effects. For a file manipulation tool with zero annotation coverage, this is inadequate.

    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 with two sentences that directly address the tool's function. Every word earns its place, and it's front-loaded with the core purpose. No wasted verbiage or redundancy.

    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 file manipulation tool with 3 parameters (including nested objects), no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on behavior, error handling, return values, and practical usage scenarios, leaving significant gaps for an AI agent.

    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 33% (low), but the description adds minimal value beyond the schema. It mentions 'Find content by search pattern, insert at marker location,' which loosely maps to source.start_pattern and target.marker, but doesn't explain parameter interactions, defaults, or edge cases. The description partially compensates for low schema coverage but not sufficiently.

    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: 'Copy/paste content between files using text patterns.' It specifies the verb (copy/paste), resource (content between files), and mechanism (text patterns). However, with no sibling tools provided, it cannot demonstrate differentiation from alternatives.

    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 only describes what the tool does, not when it's appropriate. With no sibling tools, it cannot offer comparative advice.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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