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pyzack

SYD MCP Server

by pyzack
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion. The tool's purpose is clearly defined via its name and description.

    Naming Consistency5/5

    The tool name follows a conventional verb_noun pattern (get_batch_status). As the only tool, naming consistency is trivially maintained.

    Tool Count3/5

    At one tool, the server feels underdeveloped for a general-purpose MCP server. However, if the intended scope is limited to batch status retrieval, the count may be justified, though it remains borderline.

    Completeness3/5

    The tool aggregates status, traceability, and compliance into a single response, covering the immediate needs for batch information. Yet, the absence of related operations like listing batches or updating status creates notable gaps for a broader workflow.

  • Average 3.8/5 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

  • Behavior3/5

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

    With no annotations, the description must carry the full burden of explaining behavior. It communicates a read-only intent via 'Returns' and describes the content of the response, but it does not disclose error behavior, permissions, or any side effects. The minLength and example in the schema cover parameter validation, but beyond that the behavioral picture is sparse. Still, for a simple getter, this is adequate.

    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, well-structured sentence that is efficiently front-loaded with the verb and resource, and the parenthetical enumerates what is returned without any filler. Every word contributes to understanding the tool's purpose.

    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 one required parameter and no output schema, the description adequately indicates what will be returned (status, traceability, compliance), which is the key contextual information an agent needs. It doesn't specify the return structure, but the parenthetical gives a reasonable expectation. The simplicity of the tool makes this sufficient.

    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 already fully describes the sole parameter 'batch_id' with a clear example and type. The description adds no new semantic information beyond referencing the batch ID again. Since schema coverage is 100%, a 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 tool's function with a specific verb ('Returns') and a specific resource ('SYD Digital Twin') scoped to a batch ID, and enumerates the key deliverable aspects (status, traceability, compliance). Even without sibling tools, the purpose is unambiguous and distinct.

    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?

    The usage context is implicit: the tool should be used when you have a batch ID and need its digital twin information. However, there is no explicit guidance about when not to use it, prerequisites, or alternatives. Since there are no sibling tools, some inference is required, but the description gives no direct directives.

    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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