Skip to main content
Glama

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v2.6.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: copy writes, paste reads with formatting, list_formats discovers formats, and read_raw provides raw access. No overlap or ambiguity.

    Naming Consistency5/5

    All tools follow the 'clipboard_verb_noun' pattern consistently, using snake_case with clear verbs (copy, list_formats, paste, read_raw).

    Tool Count5/5

    4 tools is well-scoped for a clipboard utility. Each tool serves a necessary function without redundancy or bloat.

    Completeness5/5

    The set covers all core clipboard operations: writing (copy), reading with formatting (paste), format discovery (list_formats), and raw access (read_raw). No obvious gaps for the domain.

  • Average 4.8/5 across 4 of 4 tools scored.

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

    • 23 of 28 community issues answered or closed in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under Apache 2.0.

  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

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

    Then . Browse examples.

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

  • Behavior4/5

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

    Adds behavioral context beyond annotations: replaces current clipboard content and returns confirmation with character count. No contradiction with 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?

    Well-structured with clear sections, concise yet informative description without 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?

    For a simple one-param tool with output schema and annotations, the description covers all needed aspects: purpose, usage, parameter meaning, and return value.

    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?

    Schema coverage is 0%, but description explains 'content' parameter as 'The text to place on the clipboard. Any string is accepted.', which compensates.

    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 explicitly states 'Copy text to the user's system clipboard' and distinguishes from sibling tools that read or list clipboard formats.

    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?

    Provides explicit when-to-call triggers (user phrases like 'copy this', and formatted output context). Lacks explicit when-not-to-call, but context is clear.

    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?

    Annotations already indicate readOnly and idempotent behavior. The description adds context about being diagnostic and the relationship to paste, but does not introduce new behavioral details beyond that. No contradictions.

    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 concise (four sentences) with no redundancy. It front-loads the primary action and efficiently provides usage guidance and output description.

    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 simple tool with no parameters and an output schema, the description sufficiently covers purpose, usage context, and output format. It is complete for the tool's complexity.

    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?

    There are no parameters (schema coverage 100%), so baseline is 4. The description adds no parameter info, but that's appropriate. It does describe the output, which adds value.

    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 function: 'List the MIME types / formats currently on the system clipboard.' It distinguishes it from siblings by explicitly saying it's a 'Diagnostic tool — use clipboard_paste to actually read and return clipboard content.'

    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 guidance: it's for diagnostic purposes, recommends clipboard_paste for actual content retrieval, and hints at what to expect for different data types (e.g., 'text/html' for spreadsheet).

    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?

    Beyond annotations (readOnlyHint, etc.), the description details handling of various content types (tables, text, code, images), table auto-detection, and return format, with no contradictions.

    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?

    Well-structured with summary, usage section, and parameter details, but slightly lengthy; still efficient and front-loaded with key purpose.

    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?

    Covers all needed context: how to call, content types handled, parameter behavior, and return type (including image handling), sufficient for proper agent use without output schema.

    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?

    Despite 0% schema description coverage, the description fully explains both parameters: output_format with all options and defaults, and include_schema with its effect, compensating effectively.

    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 it reads the clipboard and returns content, and positions itself as the primary clipboard tool, distinguishing it from sibling tools like clipboard_copy and clipboard_read_raw.

    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?

    Provides an extensive 'WHEN TO CALL' section with numerous example phrases, explains when to check clipboard for absent data, and explicitly instructs not to ask the user to paste.

    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?

    Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds: returns content as-is without parsing, lists supported MIME types (including those with non-text prefixes), and states binary types are rejected. This goes beyond annotations.

    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 well-structured with a clear first line stating purpose and usage recommendation, followed by details on behavior and examples. It is slightly lengthy but each sentence adds value. Could be trimmed slightly, but very effective.

    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 has one parameter, annotations, and an output schema (context signals indicate presence), the description covers all necessary aspects: purpose, usage, supported types, args, return value, and error behavior. No gaps remain.

    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?

    Input schema has only a name and default for mime_type, with 0% description coverage. The tool description provides a full argument description: explains what it is, gives common values like 'text/plain', 'text/html', etc., and clarifies supported types. This adds substantial meaning 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 it reads raw clipboard content for a specific MIME format, explicitly distinguishing itself from siblings: 'Diagnostic tool only — use clipboard_paste instead for normal clipboard access.' It also mentions clipboard_list_formats for discovering available types, making the purpose highly specific and differentiated.

    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?

    Provides explicit when-to-use instructions ('Diagnostic tool only'), recommends alternative (clipboard_paste), and advises using clipboard_list_formats first. This gives clear context and exclusion criteria.

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

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

mcp-clipboard MCP server

Copy to your README.md:

Score Badge

mcp-clipboard MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/cmeans/mcp-clipboard'

If you have feedback or need assistance with the MCP directory API, please join our Discord server