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dahlia

Clipboard MCP

by dahlia
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have perfectly distinct purposes: one reads from the clipboard and the other writes to it. There is no overlap or ambiguity in their functions, making it impossible for an agent to confuse them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (read_clipboard, write_clipboard) with clear action-object naming. The snake_case style is uniform throughout, making the tools predictable and easy to understand.

    Tool Count3/5

    With only two tools, the server feels minimal but functional for basic clipboard operations. While it covers the essential read/write actions, it might be considered thin for a broader utility scope, though appropriate for its focused purpose.

    Completeness4/5

    The tools provide complete CRUD-like coverage for clipboard text operations (read and write), with no dead ends. A minor gap exists in handling non-text data or advanced features like clipboard history, but core functionality is well-covered.

  • Average 4.4/5 across 2 of 2 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • This repository is licensed under AGPL 3.0.

  • 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

  • Behavior3/5

    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 explains the core behavior ('Copies the provided text to the system clipboard, making it available for pasting in other applications') and mentions the return value, but doesn't cover potential limitations like text size constraints, platform-specific behavior, or error conditions. It adequately describes the basic operation but lacks depth about edge cases.

    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 well-structured and appropriately sized. It begins with a clear purpose statement, follows with additional context about clipboard functionality, then provides specific sections for arguments and returns. Every sentence adds value without redundancy, and the information is front-loaded with the most important details first.

    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 (single parameter, no annotations, but has output schema), the description is reasonably complete. It explains what the tool does, how to use it, and what to expect in return. The output schema existence means the description doesn't need to detail return values, and it provides adequate context for basic clipboard writing functionality.

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

    Parameters4/5

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

    The description adds meaningful context for the single parameter 'text' by explaining it's 'The text content to write to the clipboard,' which provides semantic understanding beyond the schema's basic type information. With 0% schema description coverage and only one parameter, the description effectively compensates by clarifying what the parameter represents.

    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's purpose with a specific verb ('Write') and resource ('text content to the system clipboard'), and distinguishes it from its sibling 'read_clipboard' by focusing on output rather than input. The first sentence directly answers what the tool does.

    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 for when to use this tool ('to write text to the clipboard'), but doesn't explicitly mention when not to use it or compare it to alternatives. The existence of 'read_clipboard' as a sibling implies a complementary relationship, but no explicit guidance is given about choosing between them.

    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 explaining key behaviors: it returns text content, handles empty/non-text cases by returning an empty string, and describes the return value. It doesn't mention potential permissions or system-specific limitations, leaving some gaps.

    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 and front-loaded: the first sentence states the core purpose, followed by two sentences explaining return behavior. Every sentence adds essential value with zero waste or redundancy.

    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?

    Given the tool's simplicity (0 parameters, no annotations, but with an output schema), the description is complete: it explains what the tool does, when it's used, and behavioral details like empty/non-text handling. The output schema will cover return structure, so no need to elaborate further.

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

    Parameters4/5

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

    The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents this. The description appropriately doesn't add parameter details, maintaining focus on functionality. A baseline of 4 is given since no parameters exist to explain.

    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 text content from the system clipboard'), distinguishing it from its sibling 'write_clipboard' which performs the opposite operation. The purpose is unambiguous and well-defined.

    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 (to retrieve clipboard text) and implicitly contrasts with 'write_clipboard' for setting clipboard content. However, it doesn't explicitly name the alternative or provide exclusion criteria, which prevents a perfect 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 there are no obvious security issues.
  • Evaluate tool definition quality.

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