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MCP Icon Generator

by chacebot
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Local

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools are clearly distinct: generate_app_icon creates a single custom icon, while generate_ios_app_icon_set produces a complete iOS icon set from an existing source icon. There is no functional overlap; each serves a different stage in the icon creation workflow.

    Naming Consistency5/5

    Both tools follow a consistent 'generate_' prefix with a descriptive object ('app_icon', 'ios_app_icon_set'). This creates a predictable and recognizable naming pattern that aligns with common MCP server conventions.

    Tool Count3/5

    With only two tools, the server feels lightweight and minimally scoped. While the pair covers a specific workflow (single icon generation then iOS set creation), the count is at the lower boundary of what is reasonable and may be insufficient for broader icon generation needs.

    Completeness2/5

    The server name 'MCP Icon Generator' suggests a general-purpose icon generation tool, yet it only supports iOS icon sets. There is no Android, web favicon, or other platform support, and no functionality to resize or convert existing icons beyond the iOS set. This leaves significant gaps for a generic icon generator.

  • 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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
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  ]
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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 of behavioral disclosure. It only says 'generate' without revealing that the tool writes a file to outputPath, whether it overwrites existing files, or what the output/return behavior is. This is a significant transparency gap for a tool that performs a file-side effect.

    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 concise sentence with no wasted words. It is front-loaded with the core purpose, though it could arguably add a bit more detail without becoming verbose.

    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 7 parameters, no output schema, and no annotations, the description is too minimal to be fully contextual. It omits behavioral details like file saving, overwrite behavior, or any guidance on output, leaving significant gaps for an agent to infer.

    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%, providing full meaning for all 7 parameters. The description adds only a high-level mention of text, colors, and size, which overlaps with schema. Baseline 3 is appropriate since the schema already 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 tool generates an app icon image with custom text, colors, and size, using a specific verb and resource. However, it does not explicitly distinguish itself from the sibling tool generate_ios_app_icon_set, so it lacks explicit sibling differentiation.

    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 generate_ios_app_icon_set, nor does it mention any context, prerequisites, or exclusions. It simply states what the tool does without indicating appropriate use cases.

    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?

    With no annotations, the description must disclose side effects. It states the output (a complete AppIcon set) but does not mention whether it creates or overwrites files in 'appiconsetPath', what dependencies exist, or how the text/color parameters relate to the claimed 'source icon'. This leaves important behavior undisclosed.

    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, front-loaded sentence with no filler. It efficiently communicates the high-level purpose in minimal words, making it easy to scan. The minor inaccuracy in 'source icon' is a semantic issue, not a structure or conciseness issue.

    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 (5 parameters, side-effectful file writing), no annotations, and no output schema, the description is too short to be complete. It lacks crucial context about the target directory behavior, when to use this instead of the sibling, and how the text parameters map to the generated icon.

    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 has 100% description coverage for all parameters, so the baseline is 3. The tool description adds no parameter-level details beyond that, and the mention of 'single source icon' does not match any parameter in the schema, so it provides no additional semantic value.

    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 identifies the action ('Generate') and the specific deliverable ('a complete iOS AppIcon.appiconset with all required sizes'). It implicitly distinguishes itself from the sibling by emphasizing completeness, but the phrase 'from a single source icon' is confusing because the schema only contains text and color parameters, not an icon file.

    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?

    There is no guidance about when to use this tool versus the sibling tool 'generate_app_icon', nor any mention of prerequisites, alternatives, or exclusions. The description only states what it does, not when to choose it.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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