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tahir-manzoor

Aspose MCP Catalog Orchestrator

by tahir-manzoor
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Python
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Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.3.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion. The tool's purpose is clearly distinct by default.

    Naming Consistency5/5

    The single tool name follows a clear verb_noun pattern (update_product_mcp), which is consistent and predictable.

    Tool Count2/5

    One tool for a catalog orchestration server is far too few; the scope implies a broader workflow requiring multiple management actions.

    Completeness1/5

    Only an update proposal tool is provided, with no listing, retrieval, deletion, or approval operations. This severely under-covers the stated orchestration domain.

  • Average 3.2/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 2 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • 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

  • Behavior3/5

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

    With no annotations, the description carries the behavioral disclosure burden, and it does disclose a key trait: the update is proposed, not directly applied, and is described as 'validated.' However, it does not mention required permissions, post-review behavior, side effects, or what validation entails.

    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?

    One compact sentence, front-loaded with the action and outcome. There is no filler, repetition, or irrelevant detail.

    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 7 parameters, no annotations, and no output schema, this description is not complete enough to ensure correct invocation: it omits parameter guidance, validation behavior, approval workflow mechanics, and the proposal outcome. It is sufficient only to signal high-level intent.

    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%, and the description offers only the generic phrase 'product or platform MCP metadata update,' which maps loosely to product/platform but does not explain any of the 7 parameters, their constraints, or why requested_by is required. The schema property names and enum are the only parameter documentation.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description uses a specific verb ('Propose') and a concrete resource ('product or platform MCP metadata update'), and adds the qualifier 'for human review.' It clearly communicates the tool's role in an approval workflow, though the exact meaning of 'MCP metadata' is somewhat assumed.

    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 phrase 'for human review' implies this tool is for submitting proposals rather than applying changes directly, but the description gives no explicit when-to-use or when-not-to-use conditions, prerequisites, or alternatives. Usage context is implied rather than fully stated.

    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.

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Aspose MCP Catalog Orchestrator MCP server – quality and maintenance score on Glama

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