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zueai

webdev-mcp

by zueai
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Server Quality Checklist

50%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: listScreens identifies available screens for capture, while takeScreenshot performs the actual screenshot operation on a specified screen. There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool based on the task.

    Naming Consistency2/5

    The naming is inconsistent: listScreens uses camelCase, while takeScreenshot uses camelCase but with a different verb style (list vs. take). Although both are camelCase, the lack of a uniform verb_noun pattern (e.g., list_screens, take_screenshot) and mixed verb conventions reduce predictability and readability.

    Tool Count2/5

    With only 2 tools, the server feels too thin for the web development domain implied by the name 'webdev-mcp'. This limited set lacks essential operations such as screen recording, window management, or other common web development tasks, making it insufficient for comprehensive coverage.

    Completeness2/5

    The tool surface is significantly incomplete for a web development server. While listScreens and takeScreenshot cover basic screenshot functionality, there are obvious gaps like capturing specific windows, recording screen activity, or integrating with web development workflows (e.g., browser automation, code editing). This will likely cause agent failures in broader tasks.

  • Average 3.7/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

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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 full burden. It mentions the purpose but fails to disclose behavioral traits such as whether the list is real-time or cached, if it requires permissions, what format the output is in, or any rate limits. This leaves the agent with insufficient information to predict tool behavior accurately.

    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, front-loading the core action and purpose. Every element ('List available screens/displays that can be captured') directly contributes to understanding, making it optimally 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the return values are (e.g., list format, screen identifiers), behavioral aspects like permissions or freshness, or error handling. For a tool with zero structured metadata, this leaves significant gaps in agent understanding.

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

    Parameters4/5

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

    With 0 parameters and 100% schema description coverage, the baseline is high. The description adds value by clarifying that the screens are 'available' and for 'capture,' which provides context beyond the empty schema. However, it doesn't detail output semantics, slightly limiting its utility.

    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 ('List') and resource ('available screens/displays'), specifying that these are for capture purposes. It distinguishes from the sibling 'takeScreenshot' by focusing on enumeration rather than action. However, it doesn't explicitly differentiate scope or limitations beyond the capture context, keeping it from a perfect score.

    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?

    Usage is implied by mentioning 'that can be captured,' suggesting this tool should be used before 'takeScreenshot' to identify targets. No explicit guidance on when not to use it or alternatives is provided, and it lacks prerequisites or error conditions, leaving gaps in decision-making context.

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

  • Behavior3/5

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

    With no annotations provided, the description carries the full burden. It discloses the output behavior (returns base64 encoded string) and implies a capture action, but lacks details on permissions needed, potential side effects (e.g., screen flicker), error conditions, or rate limits. It's adequate but has gaps for a tool that interacts with system resources.

    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 front-loads the core action and output. Every word earns its place, with no redundancy or unnecessary elaboration, 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.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's moderate complexity (capturing screenshots with two parameters), no annotations, and no output schema, the description is reasonably complete. It covers the purpose, output format, and references a sibling tool, but could benefit from more behavioral context (e.g., permissions or errors) to be fully comprehensive.

    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%, so the schema already fully documents both parameters (screenId and timeout). The description adds no additional parameter semantics beyond what's in the schema, such as format details or constraints. Baseline 3 is appropriate when the schema does all the work.

    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 ('Take a screenshot') and resource ('of a specific screen'), and distinguishes from the sibling tool 'listScreens' by mentioning it for finding available screens. It's precise about the verb, target, and output format.

    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 by referencing the sibling tool 'listScreens' to find screen IDs, which implies when to use this tool (after identifying screens). However, it doesn't explicitly state when not to use it or name alternatives beyond the implied workflow.

    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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