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gorbabor

mc-iclone8-ui-mcp

by gorbabor

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct aspect: screen capture, visible state reading, workflow control, application inspection, and accessibility tree inspection. No ambiguity exists between their purposes.

    Naming Consistency5/5

    All tool names follow a consistent pattern: <scope>.<action> with snake_case action names (e.g., ui.capture_screen, scene.read_visible_state).

    Tool Count5/5

    With 5 tools covering capture, state, workflow, and inspection, the count is well-scoped for a UI monitoring server.

    Completeness4/5

    Covers capture, state reading, and two inspection methods, plus workflow stop. Missing tools for starting workflows or retrieving detailed element properties, but serves its monitoring purpose adequately.

  • Average 3.3/5 across 5 of 5 tools scored.

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

    • No community issues in the last 6 months
    • 16 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 Apache 2.0.

  • 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?

    No annotations are provided, so the description carries the full burden. It discloses that the operation is read-only ('Lit'), but does not mention any side effects, permissions, or output format. For a simple read tool, this is minimal but not sufficiently transparent.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single sentence that is front-loaded with the action. It is concise and to the point, but lacks any structural formatting (e.g., bullet points). It earns its place without redundancy.

    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?

    Given no parameters, no output schema, and a minimal description, the tool is borderline adequate for a simple read operation. However, the description does not clarify what the 'visible state' entails or how to interpret the output, leaving some ambiguity for the agent.

    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?

    There are zero parameters, and the schema description coverage is 100% (empty). According to guidelines, baseline score is 4 for no parameters. The description adds no parameter information since none exist.

    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 that the tool reads the known visible state of the iClone 8 interface, using a specific verb and resource. It distinguishes itself from sibling tools like ui.capture_screen, though it is in French, which may reduce clarity for non-French-speaking agents.

    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?

    No guidance is provided on when to use this tool versus alternatives (e.g., ui.inspect_application or ui.capture_screen). The description only states what it does without context or exclusions.

    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?

    No annotations are provided, so the description carries the full burden. It discloses that the capture does not modify the scene, which is important. However, it does not explain output behavior (e.g., file saving, format, error handling).

    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?

    A single sentence that efficiently conveys purpose and a key behavioral trait. No wasted words.

    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 2 parameters and no output schema or annotations, the description is insufficient. It does not explain parameter usage, output details, prerequisites, or error conditions. A screenshot tool typically requires more context.

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

    Parameters1/5

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

    Schema description coverage is 0%, and the description adds zero information about parameters. The 'path' and 'window_only' parameters are not explained beyond their schema types.

    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 action ('capture') and resource ('screen or iClone 8 window'), with a key property ('without modifying the scene'). It distinctly separates from sibling tools like scene.read_visible_state or ui.inspect_application.

    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?

    No guidance on when to use this tool versus alternatives. The description lacks any usage context or exclusions.

    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?

    The description mentions that no action is performed (safe read-only operation), which is helpful. However, with no annotations, it should also disclose potential impacts on UI state, performance considerations, or timeouts. Missing details on return format.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Single sentence, no fluff. Could be slightly more informative without losing conciseness.

    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 tool with one optional parameter, the description is minimally adequate. It lacks details about output format and how to interpret results, but sibling tools are sufficiently different to avoid confusion.

    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 does not mention the single parameter `max_elements`, but the schema provides clear constraints and default. Since schema coverage is 0%, the description could add context (e.g., why limit), but it's not critical.

    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 it reads UI Automation controls without performing any action, which distinguishes it from sibling tools like ui.capture_screen and workflow.stop_all. However, it could be more specific (e.g., 'accessibility tree' vs 'controls').

    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?

    No guidance on when to use this tool vs alternatives like ui.inspect_application. The description does not provide any usage context or exclusions.

    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?

    The phrase 'arrêt propre' (clean stop) is vague and does not explain the behavioral implications such as whether the stop is graceful or forceful, whether state is saved, or if it has side effects. No annotations are provided to compensate.

    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 sentence that is concise and front-loaded with the core action. No wasted words.

    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 tool with no parameters and no output schema, the description is minimally adequate. However, it does not clarify the return value or confirm whether the stop is asynchronous or synchronous, which could affect agent decision-making.

    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?

    There are no parameters, so schema coverage is 100%. The description adds no additional information about parameters, but none is required. Baseline of 3 is appropriate.

    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 identifies the action (stop) and the resource (current UI workflow). It uses a specific verb and resource, and the tool's purpose is distinct from all sibling tools which are read/inspection tools.

    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?

    No guidance on when to use or not use this tool. No mention of prerequisites (e.g., must have a running workflow) or alternatives. The description is purely a statement of function.

    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 full burden. It correctly states 'en lecture seule' (read-only), indicating no mutation, but does not explain what the inspection returns or whether it has side effects beyond reading.

    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 without extraneous information. It is front-loaded and every word adds value.

    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?

    For a tool with no parameters, no output schema, and no annotations, the description provides only minimal information. It does not explain what 'inspect' yields (e.g., window properties, hierarchy) or how to interpret the output.

    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?

    There are zero parameters, and schema description coverage is 100%. The description does not need to add parameter information, and baseline of 4 is appropriate.

    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 uses a specific verb ('Inspecte') and resource ('fenêtres visibles iClone 8') with a qualifier ('en lecture seule'), clearly distinguishing from sibling tools like ui.capture_screen and scene.read_visible_state.

    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?

    No guidance is given on when to use this tool instead of alternatives like ui.inspect_accessibility_tree or ui.capture_screen. The description does not mention context or exclude scenarios.

    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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