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ravinahp

Surf MCP Server

by ravinahp

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 ambiguity or overlap between tools. The tool's purpose is clearly defined as retrieving tide information for a specific location and date, making it distinct by default.

    Naming Consistency5/5

    The single tool follows a clear verb_noun pattern (get_tides), which is consistent and predictable. Since there are no other tools to compare against, the naming convention is perfectly uniform.

    Tool Count2/5

    A single tool is too few for a server named 'Surf MCP Server', which implies a broader scope related to surfing or ocean conditions. This minimal toolset feels incomplete and under-scoped for the apparent domain.

    Completeness2/5

    The tool surface is severely incomplete for a surfing-related server. While get_tides covers tide information, there are obvious gaps such as wave forecasts, weather data, or surf spot details, which are essential for the domain and will likely cause agent failures.

  • Average 3.4/5 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 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. While it mentions what the tool returns ('Formatted string containing tide information and station details'), it lacks critical behavioral context such as rate limits, error conditions, authentication requirements, or whether this is a read-only operation. The description provides basic output format but misses important operational details.

    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 perfectly structured and concise. It begins with a clear purpose statement, then provides organized sections for arguments and returns with specific formatting details. Every sentence adds value, and the information is front-loaded with the most important details first.

    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 3-parameter tool with no annotations and no output schema, the description provides adequate but incomplete coverage. It explains parameters well and gives output format, but lacks behavioral context like error handling, rate limits, or authentication requirements. The absence of an output schema means the description should ideally provide more detail about the return structure beyond 'formatted string.'

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description provides excellent parameter semantics despite 0% schema description coverage. It clearly explains each parameter's purpose: 'Float value representing the location's latitude/longitude' and 'Date string in YYYY-MM-DD format.' This fully compensates for the lack of schema descriptions and adds meaningful context beyond what the bare schema provides.

    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 tide information for a specific location and date.' It uses a specific verb ('Get') and resource ('tide information'), and specifies the scope ('for a specific location and date'). However, with no sibling tools provided, there's no opportunity to differentiate from alternatives, preventing a perfect score of 5.

    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, prerequisites, or constraints. It simply states what the tool does without any context about appropriate usage scenarios. With no siblings listed, this omission is less critical but still represents a gap in guidance.

    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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