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lincw

CWA MCP Server

by lincw
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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 tool has a single, clear purpose: retrieving weather forecasts for specific locations in Taiwan.

    Naming Consistency5/5

    The single tool name 'get_weather_forecast' follows a clear verb_noun pattern (get + weather_forecast). Since there's 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 current conditions, forecasts, alerts, or location searches. This minimal surface suggests the server is underpowered for comprehensive weather interactions.

    Completeness2/5

    The server is severely incomplete for a weather domain, offering only a 36-hour forecast retrieval. It lacks essential operations such as current weather, extended forecasts, severe weather alerts, or location-based searches, which will limit agent capabilities significantly.

  • Average 3.7/5 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
    • Last stable release on
    • 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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what the tool does but lacks details on behavioral traits such as rate limits, error handling, authentication needs, or what the output format looks like. This leaves gaps in understanding how the tool behaves beyond its basic function.

    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 appropriately sized and front-loaded, starting with the core purpose and followed by essential details (time frame and locations). Every sentence earns its place by providing necessary information without redundancy, making it efficient and easy to understand.

    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?

    Given the tool's low complexity (one parameter, no output schema, no annotations), the description is complete enough for basic usage but lacks details on output format and behavioral aspects. It covers the what and where adequately but falls short on how the tool behaves and what results to expect.

    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 description coverage is 100%, with the parameter 'locationName' fully documented in the schema. The description adds value by listing all available locations, which provides semantic context beyond the schema's generic description, but does not elaborate further on parameter usage or constraints.

    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 specific action ('Get Taiwan weather forecast'), resource ('weather forecast'), scope ('next 36 hours'), and geographical constraint ('by county/city name'). It distinguishes itself by specifying the exact time range and available locations, making the purpose unambiguous and comprehensive.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides clear context for when to use this tool by specifying the geographical scope (Taiwan), time frame (next 36 hours), and available locations. However, it does not mention when not to use it or any alternatives, as there are no sibling tools provided, so explicit exclusions are not necessary but could be implied.

    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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  • Evaluate tool definition quality.

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