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randa-mu

drand-mcp-server

by randa-mu
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TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v0.0.1-rc1

  • Disambiguation5/5

    Each tool requires a distinct input: round number, timestamp, or no input for latest. There is no overlap in purpose, making it easy for an agent to select the correct tool.

    Naming Consistency5/5

    All tool names follow the consistent pattern 'get-randomness-by-{criteria}', using hyphenated lowercase. The naming is predictable and clear.

    Tool Count5/5

    Three tools is appropriate for a focused server that retrieves randomness from drand. The count is not excessive nor insufficient for the domain.

    Completeness4/5

    The tools cover the primary ways to fetch randomness (by round, by time, latest). One could argue for a tool to list available rounds, but the current set is functionally complete for the server's purpose.

  • Average 3.5/5 across 3 of 3 tools scored. Lowest: 2.9/5.

    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 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.

  • 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.

  • Add related servers to improve discoverability.

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, the description carries full burden. It only says 'Get', implying a read operation, but does not disclose any side effects, error behavior, authentication needs, or what happens for invalid rounds. Minimal behavioral info.

    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 sentence with no wasted words. However, there is a typo ('specfic' instead of 'specific'), which slightly reduces clarity.

    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 simple tool with one parameter and no output schema, the description should explain what 'round' means and what the return value is. It does not mention that 'drand quicknet' is a specific network or describe the output format. Incomplete.

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

    Parameters2/5

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

    Schema coverage is 0% (parameter has no description). The description only implies the 'round' parameter via the resource name but does not explain its meaning, format, or constraints. Does not compensate for the lack of schema detail.

    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 'Get the random value associated with a specific round from drand quicknet', which includes a verb and specific resource. It distinguishes from siblings ('get-randomness-by-time' and 'get-randomness-latest') by specifying input is a round.

    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?

    No guidance is provided on when to use this tool versus the siblings. The description does not mention alternatives or conditions for usage.

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

  • Behavior3/5

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

    With no annotations, the description carries the full burden. It only states that it retrieves a random value but does not disclose potential errors, uniqueness constraints, or output format. Minimal transparency.

    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 a single, concise sentence that conveys the purpose without extra words. It is front-loaded and efficient.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the simple nature of the tool (one parameter, no output schema), the description is partially complete. It lacks detail on parameter format and return value, but covers the basic purpose.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must compensate. However, it only loosely refers to 'a specific time' without explaining the format (Unix timestamp, milliseconds, etc.) or the unit of the number parameter.

    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 verb (Get), the resource (random value), and the context (associated with a specific time from drand quicknet). It effectively distinguishes this tool from its siblings (by-round and latest) by specifying 'by time'.

    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?

    While the context implies use when you have a specific time, there is no explicit guidance on when to use this tool over alternatives, nor any prerequisites or limitations mentioned.

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

  • Behavior2/5

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

    No annotations are provided, and the description only states the basic action. It does not disclose behavioral traits such as whether the tool is read-only (assumed), if it has any rate limits, or what happens on error. For a tool with no annotations, the description should carry more behavioral context.

    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 a single sentence of 8 words, perfectly sized for the tool's simplicity. It is front-loaded and contains no superfluous information.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's low complexity (no parameters, simple fetch), the description gives the core idea but lacks details about the output structure. Since there is no output schema, the description could have briefly noted the response format (e.g., round number, randomness 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?

    The tool has zero parameters, so schema coverage is trivially 100%. The description does not add parameter details because none exist. With no parameters, a baseline of 4 is appropriate as the description does not detract from 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 the action ('Get'), resource ('latest random value'), and source ('drand quicknet'). It distinguishes itself from sibling tools 'get-randomness-by-round' and 'get-randomness-by-time' by focusing on the latest value.

    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 implies usage for obtaining the most recent randomness, but does not explicitly state when to use this tool over siblings or provide exclusions. The context is clear from the name and description, but lacks explicit guidance.

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

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