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radial-hks

MCP Server PROJ

by radial-hks
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one transforms coordinates between systems, the other lists supported coordinate systems. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow a consistent verb-noun pattern with hyphenated lowercase (transform-coordinates, list-supported-crs), making the naming predictable and easy to understand.

    Tool Count3/5

    With only two tools, the server feels thin for a coordinate transformation service. While they cover a minimal workflow, the count is borderline and could be expanded with additional useful operations.

    Completeness4/5

    The core workflow is covered: users can list supported CRS and transform coordinates between them. Minor gaps exist, such as retrieving detailed CRS metadata or more advanced PROJ operations, but the basics are functional.

  • Average 3.5/5 across 2 of 2 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.

  • 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.

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  "$schema": "https://glama.ai/mcp/schemas/server.json",
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  ]
}

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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

  • Behavior2/5

    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 merely states the listing action but does not mention return format, potential errors, or whether the operation is read-only (though that is implied). The description adds no behavioral context beyond the purpose.

    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, short sentence that is immediately understandable. It wastes no words and is well-structured, with the key action and object front-loaded.

    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?

    The tool is simple with no parameters and no output schema. The description covers the core purpose, but it does not specify the structure of the returned list (e.g., array of codes, names, or objects), which would be helpful for an agent to correctly parse the output. It is adequate for a basic list tool but leaves a minor gap.

    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, and the baseline for such tools is 4. The description does not need to explain parameter semantics since none exist, and the schema correctly reflects an empty object.

    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 clearly states a specific verb and resource: 'List all supported coordinate systems.' While it does not explicitly differentiate from the sibling tool 'transform-coordinates', the purpose is unambiguous and distinct in intent.

    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?

    The description provides no guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent to infer usage solely from the tool's name.

    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 does disclose the supported CRS formats, which is helpful, but it omits other behavioral details such as whether the operation is read-only, what the return value looks like, or how errors are handled. For a transformation tool, the core behavior is evident, but more context would improve 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 is front-loaded with the core purpose and supported formats. Every word earns its place, with no filler or redundancy.

    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?

    The tool has moderate complexity, but the description does not explain the return format or coordinate structure, which is significant given the absence of an output schema. The schema provides some parameter details, but the overall description remains incomplete for a tool that transforms geospatial data.

    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?

    Schema coverage is 67%; the CRS parameters have detailed descriptions in the schema, and the description repeats these formats without adding new meaning. The coordinates parameter lacks a schema description, and the tool description does not compensate by explaining the expected format or structure for coordinates.

    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 transforms coordinates between different coordinate systems, which is a specific verb+resource. It also lists the supported CRS formats (EPSG, WKT, Proj), distinguishing it from the sibling 'list-supported-crs' tool.

    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 description implies usage when coordinate conversion is needed, but it offers no explicit guidance on when to use this tool versus alternatives, nor does it state any exclusions. It relies on the user to infer purpose from the function name.

    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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