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juliengrelet

Wisembly MCP Server

by juliengrelet
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TypeScript
Remote

Server Quality Checklist

50%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one fetches event data by keyword, while the other fetches session data by event ID. There is no overlap or ambiguity between them, making it easy for an agent to select the correct tool based on the input parameter.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'get_wisembly_' prefix, using snake_case throughout. The naming is predictable and readable, with no deviations in style or convention.

    Tool Count2/5

    With only 2 tools, the server feels thin for a Wisembly API integration. This minimal set lacks essential operations like creating, updating, or deleting events/sessions, limiting its utility for comprehensive agent workflows in this domain.

    Completeness2/5

    The tool surface is severely incomplete for a Wisembly API server. It only provides read operations (get_event and get_sessions), missing critical CRUD functionality such as create_event, update_event, delete_event, and session management operations, which are essential for full lifecycle coverage.

  • Average 2.9/5 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Fetch event data' but doesn't describe traits like read-only vs. destructive, authentication needs, rate limits, error handling, or response format. The description adds minimal context beyond the basic action, leaving significant gaps in understanding how the tool behaves.

    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 with zero waste: 'Fetch event data from the Wisembly API for any keyword'. It is appropriately sized and front-loaded, clearly stating the core purpose without unnecessary details. Every word earns its place, making it highly concise and well-structured.

    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 tool's complexity (a read operation with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'event data' includes, how results are returned, or any behavioral traits. For a tool fetching data from an API, more context on response format and usage constraints is needed to be fully helpful.

    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 input schema has 100% description coverage, with the parameter 'keyword' documented as 'The keyword to search for in the Wisembly API'. The description adds no additional meaning beyond this, as it only repeats 'any keyword' without elaborating on format, examples, or constraints. Baseline 3 is appropriate since the schema does the heavy lifting.

    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 action ('Fetch') and resource ('event data from the Wisembly API'), specifying it's for 'any keyword'. It distinguishes from the sibling tool 'get_wisembly_sessions' by focusing on events rather than sessions, though it doesn't explicitly mention this distinction. The purpose is specific but could be more precise about what 'event data' entails.

    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, such as the sibling tool 'get_wisembly_sessions'. It mentions 'any keyword' but doesn't specify contexts, prerequisites, or exclusions. Usage is implied only through the tool name and description, lacking explicit instructions for selection.

    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 the full burden. It mentions 'fetch' which implies a read operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, error handling, or what the output looks like (especially since there's no output schema). 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 with no wasted words. It's appropriately sized and front-loaded with the core purpose, making it easy to parse quickly.

    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 'sessions data' includes, how results are returned, or any behavioral constraints. For a tool fetching data from an API, this leaves too many unknowns for effective agent use.

    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%, so the schema already documents the single parameter 'keyword' as 'The keyword to search for in the Wisembly API'. The description adds 'by event id', which might imply a relationship between 'keyword' and 'event id', but this is ambiguous and doesn't clearly enhance the schema's information. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 action ('fetch') and resource ('sessions data from the Wisembly API'), making the purpose understandable. However, it doesn't differentiate from the sibling tool 'get_wisembly_event' beyond mentioning 'by event id', which is somewhat vague about how it relates to the sibling.

    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 minimal guidance with 'by event id', but it doesn't explicitly state when to use this tool versus the sibling 'get_wisembly_event', nor does it mention any prerequisites or alternatives. This leaves the agent with little context for tool selection.

    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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