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itachiuchihadev

weather-mcp-server

by itachiuchihadev
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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. Every tool (the only tool) has a clearly distinct purpose.

    Naming Consistency5/5

    The single tool name 'get_weather' follows a consistent verb_noun pattern, which is a standard and clear convention. There are no other tools to create inconsistency.

    Tool Count2/5

    The server has exactly one tool, which feels too thin for the apparent scope of a weather service. While the tool covers current and forecast data, a typical weather server might offer additional operations like alerts or historical data.

    Completeness4/5

    The single tool covers the core weather use case of current conditions and 1-7 day forecast. Minor gaps exist—such as weather alerts, historical data, or multi-location retrieval—but they are not essential to the primary purpose.

  • 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
    • 4 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 ISC License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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 carries the full burden of behavioral disclosure. It reveals the core behavior (current weather and forecast range) but omits details such as response format, error handling, or data source. This partial disclosure is adequate but not fully transparent.

    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, focused sentence that immediately communicates the tool's purpose. It is concise, front-loaded, and contains no unnecessary words.

    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 simple tool with a well-documented schema, the description covers the essential function and scope. However, the absence of an output schema and lack of mention of return values or edge cases leave minor gaps, though they are not critical for a basic weather lookup.

    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 schema provides complete descriptions for both parameters, including examples and default values. The tool description adds no new semantic information beyond what the schema already covers, so 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.

    Purpose5/5

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

    The description states the tool retrieves current weather and a 1-7 day forecast for a specific location, using a clear verb ('get') and a specific resource ('weather'). It unambiguously defines what the tool does without ambiguity.

    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?

    There are no sibling tools or explicit alternative mentioned, and the description does not state when to use this tool versus others. It implies usage for weather requests but provides no exclusions or prerequisites, leaving the guidance implicit.

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

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