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gaurigshankar

Weather MCP Server

by gaurigshankar
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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

    The two tools have clearly distinct purposes: one retrieves weather alerts for a state, while the other provides forecasts for a location. There is no overlap in functionality or ambiguity between them, making it easy for an agent to select the correct tool based on the need.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'get_' as the prefix, ensuring predictability and readability. The naming is uniform across the set, with no deviations in style or convention.

    Tool Count2/5

    With only two tools, the server feels thin for a weather domain, lacking essential operations like current conditions, historical data, or radar information. This minimal set may limit agent capabilities and require workarounds for common weather-related tasks.

    Completeness2/5

    The tool surface is significantly incomplete for a weather server, missing core functionalities such as current weather, hourly forecasts, or severe weather details. Agents will face gaps in handling typical weather queries, leading to potential failures or incomplete responses.

  • Average 3/5 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.

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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 states what the tool does but doesn't describe any behavioral traits such as whether it's read-only, rate-limited, authentication requirements, error conditions, or what format the alerts are returned in. This is a significant gap for a tool with no annotation coverage.

    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, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple tool with one parameter and is front-loaded with the essential information.

    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?

    Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., alert types, format, timestamps) or any behavioral aspects like error handling. For a tool with no structured metadata, the description should provide more context to be fully helpful to an agent.

    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 description doesn't add any parameter information beyond what's already in the schema, which has 100% coverage and fully documents the 'state' parameter. Since schema coverage is high, the baseline score is 3, as the description doesn't compensate but also doesn't detract from the schema's 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 clearly states the verb ('Get') and resource ('weather alerts for a state'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling tool 'get_forecast', which appears to be a related weather tool but for forecasts rather than alerts.

    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 like 'get_forecast'. It doesn't mention prerequisites, exclusions, or specific contexts where this tool is preferred, leaving the agent to infer usage based on the tool name alone.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden for behavioral disclosure. 'Get weather forecast' implies a read-only operation, but the description doesn't specify what kind of forecast data is returned (e.g., hourly/daily, temperature/precipitation), whether there are rate limits, authentication requirements, or data freshness considerations.

    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, efficient sentence that states exactly what the tool does without any unnecessary words. It's appropriately sized for a simple tool with two parameters and gets straight to the point.

    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?

    For a simple read-only tool with complete schema coverage but no output schema, the description provides the basic purpose but lacks important context. Without annotations or output schema, users don't know what format the forecast data will be in, what time periods it covers, or how to interpret the results.

    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%, with both latitude and longitude parameters well-documented in the schema. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline expectation when schema coverage is complete.

    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 verb 'get' and resource 'weather forecast for a location', making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'get_alerts', which presumably also provides weather-related information but for alerts rather than forecasts.

    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. With a sibling tool 'get_alerts' available, there's no indication of when to choose forecast data over alert data, or whether these tools should be used together or separately.

    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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