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jhupo

image-studio-mcp

by jhupo
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
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: edit_image modifies existing images based on a prompt and optional mask, while generate_image creates new images from scratch using a prompt. There is no overlap or ambiguity between these functions.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (edit_image, generate_image) with the same verb style and underscore separation. The naming is perfectly predictable and uniform.

    Tool Count2/5

    With only 2 tools, this server feels thin for an 'image studio' domain. While the tools cover basic generation and editing, there are likely missing operations like image analysis, format conversion, or batch processing that would be expected in a comprehensive image toolset.

    Completeness2/5

    For an image processing server, there are significant gaps in the surface. Missing are tools for tasks like image resizing, filtering, metadata reading, format conversion, or batch operations. The current tools only cover generation and basic editing, leaving many common image workflows unsupported.

  • Average 2.9/5 across 2 of 2 tools scored.

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

    • 0 of 1 community issues answered or closed in the last 6 months
    • No commit activity data available
    • 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.

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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 full burden for behavioral disclosure. It mentions saving to local files but doesn't cover critical aspects like rate limits, authentication needs, error handling, or what happens if files already exist. For an 11-parameter tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

    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, well-constructed sentence that efficiently conveys the core functionality without unnecessary words. It's appropriately sized and front-loaded with the essential information.

    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 complexity (11 parameters, no annotations, no output schema), the description is inadequate. It covers the basic purpose but lacks parameter explanations, behavioral context, usage guidelines, and output information. For a sophisticated image generation tool, this leaves too many unanswered questions.

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

    Parameters2/5

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

    With 0% schema description coverage for 11 parameters, the description must compensate but fails to do so. It mentions 'prompt' and 'output_dir' implicitly through the action description but doesn't explain any of the other 9 parameters like 'size', 'quality', 'background', etc. This leaves most parameters semantically undocumented.

    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 ('generate') and resource ('images'), specifying it uses an OpenAI-compatible endpoint and saves to local files. It distinguishes from the sibling 'edit_image' by focusing on generation rather than editing. However, it doesn't explicitly contrast with the sibling tool, so it's not a perfect 5.

    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 like 'edit_image'. It mentions the general context of generating images from prompts but offers no explicit when/when-not instructions or prerequisites for usage.

    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 of behavioral disclosure. While it mentions the basic operation (edit with prompt, optionally mask, save locally), it lacks critical details such as whether this is a read-only or destructive operation, what permissions or authentication might be required, rate limits, error handling, or what the output looks like (e.g., file paths, success indicators). For a tool with 12 parameters and no annotations, this is a significant gap.

    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, well-structured sentence that efficiently conveys the core functionality. It's front-loaded with the main action and includes key optional elements without unnecessary elaboration. Every word earns its place, making it highly concise.

    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 complexity (12 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the behavioral aspects (e.g., mutation effects, error handling), most parameter meanings, or what the tool returns (since there's no output schema). For a tool with this level of complexity, the description should provide more guidance to help an agent use it correctly.

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

    Parameters2/5

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

    Schema description coverage is 0%, meaning none of the 12 parameters have descriptions in the schema. The description only mentions 'prompt', 'mask', and saving to 'local files', which loosely corresponds to 'prompt', 'mask_image', and 'output_dir' parameters. It doesn't explain the purpose or usage of the other 9 parameters (e.g., 'count', 'size', 'quality', 'user'), leaving them undocumented. With low coverage, the description fails to compensate adequately.

    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 ('edit'), the target ('one or more source images'), the mechanism ('with a prompt'), and the outcome ('save the results to local files'). It distinguishes from the sibling 'generate_image' by specifying editing of existing images rather than generation from scratch. However, it doesn't specify the type of editing (e.g., inpainting, style transfer) which could make it more specific.

    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 editing existing images with a prompt, which differentiates it from 'generate_image' that presumably creates new images. However, it doesn't provide explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or constraints beyond the optional mask parameter.

    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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