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peterparker57

WSLSnapit-MCP

by peterparker57
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Server Quality Checklist

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

  • Latest release: v2.2.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one reads clipboard content (text or image), while the other captures screenshots. There is no overlap in functionality, making it impossible to confuse them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern: 'read_clipboard' and 'take_screenshot'. The naming is clear, predictable, and uses the same convention throughout.

    Tool Count2/5

    With only two tools, the server feels thin for a general-purpose utility server. While the tools are specific to clipboard and screenshot operations, the scope is limited, and more complementary tools (e.g., for image processing or file management) might be expected.

    Completeness3/5

    For a clipboard and screenshot utility, basic read/capture operations are covered, but there are notable gaps. For example, there is no tool to write to the clipboard, edit screenshots, or manage captured images, which could limit agent workflows.

  • Average 3.7/5 across 2 of 2 tools scored. Lowest: 3.1/5.

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

    • 0 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 status not available

  • This repository is licensed under MIT License.

  • 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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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 mentions the tool reads clipboard content but fails to describe important behaviors like whether it requires specific permissions, how it handles errors, what happens if the clipboard is empty, or the format of returned data. The description is minimal and lacks operational context.

    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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool, though it could be slightly more informative without sacrificing brevity.

    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 and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, how errors are handled, or any operational constraints. Given the tool's potential complexity (reading both text and images from the clipboard), more context is needed for effective use.

    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, fully documenting the single parameter 'format' with its enum values and default. The description adds no additional parameter semantics beyond what's in the schema, but since schema coverage is high, the baseline score of 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 specific action ('Read') and resource ('current Windows clipboard content'), specifying it handles both text and image formats. It distinguishes itself from the sibling tool 'take_screenshot' by focusing on clipboard access rather than screen capture.

    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, nor does it mention any prerequisites or context for usage. It simply states what the tool does without indicating appropriate scenarios or limitations.

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

  • Behavior4/5

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

    With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: 'direct image return' (output behavior), 'auto-compression' (processing behavior), and 'smart' capture with title/process matching. It doesn't mention potential side effects like screen flashing or permissions needed, but covers the core functionality adequately 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is perfectly concise - a single sentence that packs essential information: tool identity (WSLSnapIt), purpose (smart screenshot capture), context (for WSL), key features (capture options), and behavioral traits (direct return, auto-compression). Every word earns its place with zero 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?

    For a tool with 8 parameters, 100% schema coverage, and no output schema, the description provides good contextual completeness. It covers the tool's purpose, key behaviors, and context. The main gap is lack of output format details (what exactly is returned when returnDirect is true/false), but given the schema's thorough parameter documentation, this is a minor omission.

    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?

    With 100% schema description coverage, the input schema already documents all 8 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it mentions 'monitors, windows by title/process' which aligns with parameters but doesn't provide additional context. This meets the baseline of 3 when schema coverage is high.

    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 specific action ('capture'), target ('screenshot'), and context ('for WSL'). It distinguishes itself from the only sibling tool 'read_clipboard' by focusing on image capture rather than clipboard operations. The description includes key capabilities like capturing monitors/windows and direct image return with compression.

    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 provides clear context about when to use this tool ('smart screenshot capture for WSL') and implies usage scenarios through its feature list. However, it doesn't explicitly state when NOT to use it or mention alternatives to this specific screenshot tool. The sibling tool 'read_clipboard' is unrelated, so no explicit comparison is needed.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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