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dstotijn

KNMI MCP Server

by dstotijn
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TypeScript

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'get_weather' has a clear and distinct purpose, making disambiguation trivial.

    Naming Consistency5/5

    The single tool name 'get_weather' follows a clear verb_noun pattern (get + weather). Since there is only one tool, consistency is inherently perfect with no deviations to evaluate.

    Tool Count2/5

    A single tool is too few for a weather server's apparent scope, which typically involves multiple operations like forecasts, historical data, or alerts. This minimal set limits functionality and feels incomplete for the domain.

    Completeness2/5

    The tool set is severely incomplete for a weather server, covering only current weather retrieval. Obvious gaps include forecasts, historical data, alerts, or multi-location queries, which are essential for comprehensive weather-related tasks.

  • Average 3.6/5 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 Apache 2.0.

  • 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?

    The annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds value by explaining that location names are automatically converted to grid identifiers, which is useful behavioral context not covered by annotations. However, it does not disclose other potential traits like rate limits, error handling, or data freshness, leaving some gaps in transparency despite the annotation support.

    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 and well-structured, consisting of two sentences that efficiently convey the tool's purpose and key behavioral detail (automatic conversion of location names). Every sentence adds value without redundancy, and the information is front-loaded, making it easy to grasp quickly. There is no wasted verbiage or unnecessary elaboration.

    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?

    Given the tool's moderate complexity (2 parameters, 1 required), the presence of annotations (readOnlyHint), and an output schema (which handles return values), the description is reasonably complete. It covers the core functionality and a key behavioral aspect (location conversion). However, it could be more comprehensive by addressing potential limitations or usage nuances, such as the scope of supported locations or the role of the optional region parameter.

    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 description coverage is 100%, meaning the input schema fully documents both parameters (location and region). The description adds semantic context by clarifying that location names are accepted and automatically converted to grid identifiers, which enhances understanding beyond the schema's basic description. This provides some added value, but since the schema already covers the parameters well, the baseline score of 3 is appropriate.

    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 the tool's purpose: 'Get current weather information for a Dutch location.' It specifies the verb ('Get'), resource ('weather information'), and geographic scope ('Dutch location'), making it easy to understand what the tool does. However, since there are no sibling tools, it cannot demonstrate differentiation from alternatives, which prevents a perfect score.

    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 by specifying 'for a Dutch location,' which sets a geographic context. However, it does not provide explicit guidance on when to use this tool versus alternatives (e.g., other weather tools or methods), nor does it mention any exclusions or prerequisites. With no sibling tools, the lack of comparative guidance is less critical, but the description still only offers implied context without clear when/when-not instructions.

    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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