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colinterface

Bay Wheels MCP Server

by colinterface
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one locates available bikes for pickup, the other locates available return spaces. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow the consistent pattern 'find_nearest_' followed by the object ('bike' or 'dock_spaces'). This creates a predictable and coherent naming convention.

    Tool Count3/5

    With only two tools, the server feels thin but is appropriately scoped for a simple find-nearest utility. It is borderline, as it might benefit from additional tools like station list or trip planning, but it is not excessive.

    Completeness4/5

    The pair covers the two core needs of a bike-sharing user: finding bikes to rent and finding spaces to return. Minor gaps exist (e.g., station details or real-time status), but for the apparent minimal scope, it is mostly complete.

  • Average 3.9/5 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

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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. It does not disclose whether the tool is read-only, whether it returns multiple docks or just the nearest, what happens if no dock has the required spaces, or if results are sorted by distance. The description leaves key behavioral aspects open to interpretation.

    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 front-loaded with the core purpose. The parameter list is structured and avoids fluff, though it partly duplicates the schema, it earns its place by compensating for the schema's lack of descriptions.

    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 3-parameter finder with an output schema, the description is mostly complete but lacks usage guidance and behavioral edge cases. The presence of an output schema partially satisfies return value disclosure, but the absence of annotations leaves gaps in understanding tool behavior.

    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?

    With schema coverage at 0%, the description must explain parameters. It adds minimal value by restating latitude/longitude as 'search location' and specifying count as 'number of spaces needed (default 1)'. The count explanation adds meaning, but latitude/longitude descriptions are largely tautological.

    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 what the tool does: 'Find the nearest dock with at least N available return spaces.' This is a specific verb+resource+constraint and distinguishes from the sibling tool find_nearest_bike.

    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 for finding docks with return space availability but does not explicitly state when to prefer this over find_nearest_bike or provide any exclusions. No alternatives or when-not guidance is given.

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

  • Behavior4/5

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

    With no annotations, the description carries the full burden. It discloses the core behavioral logic: requiring at least N available bikes, special handling for N=1 ('free bike locations'), and optional bike type filtering. It goes beyond a simple verb-noun description, though it does not mention potential failure modes, sorting details, or what 'free bike locations' exactly entails. Given the read-only nature implied by 'Find', this is reasonably 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 highly concise: a two-sentence summary followed by a structured parameter list. Every sentence adds value, and the front-loaded core behavior is immediately understandable. No unnecessary fluff.

    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 has an output schema, the description does not need to explain return values. It explains the main behavior and all parameters, though it does not address edge cases like no available docks. The sibling tool is not mentioned, which slightly reduces completeness, but the core context is adequate for an agent to invoke the tool correctly.

    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 input schema has 0% description coverage, so the description must compensate. It provides an Args block that explains every parameter: latitude, longitude, count (with default), and bike_type (listing acceptable values and meaning of None). This fully explains the parameters beyond the schema's basic type definitions.

    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 a specific verb ('Find') and resource ('nearest dock with at least N available bikes'), including a special case for N=1. It effectively distinguishes from the sibling tool find_nearest_dock_spaces by focusing on bike availability rather than dock spaces.

    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 the tool is for finding bikes by location and count, but it does not explicitly state when to use this tool versus the sibling find_nearest_dock_spaces, nor does it provide exclusions or alternative recommendations. The usage context is clear from the description but not explicitly contrasted.

    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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