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stvlynn

Volcengine Image Generation MCP Server

by stvlynn
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TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'generate_image' has a clear and distinct purpose for generating images via a text-to-image API, leaving no ambiguity for an agent to misselect.

    Naming Consistency5/5

    The tool name 'generate_image' follows a consistent verb_noun pattern, and with only one tool, there is no inconsistency to evaluate. The naming is straightforward and predictable, adhering to common conventions without any deviations.

    Tool Count2/5

    A single tool is too few for a server focused on image generation, as it lacks essential operations like listing generated images, managing styles, or handling errors. This minimal scope limits functionality and feels incomplete for the domain, making it borderline inappropriate.

    Completeness2/5

    The tool set is severely incomplete for an image generation server. While 'generate_image' covers the core creation function, there are significant gaps such as retrieving, updating, or deleting images, managing parameters, or handling batch operations, which will likely cause agent failures in complex workflows.

  • Average 3.1/5 across 1 of 1 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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  • 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 the full burden of behavioral disclosure. It mentions the API provider but doesn't describe rate limits, authentication requirements, error handling, what happens when generation fails, or the nature of the output (e.g., image format, quality constraints). This leaves significant gaps for a generative tool.

    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 directly states the tool's purpose without any unnecessary words. It's perfectly front-loaded and wastes no space.

    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 generative image tool with 7 parameters and no output schema, the description is minimal. While concise, it doesn't compensate for the lack of annotations or output schema by explaining what kind of image data is returned, typical use cases, or limitations. The schema handles parameter documentation well, but overall context remains incomplete.

    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 adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with detailed descriptions for all 7 parameters. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't provide additional context like typical prompt structures or model selection guidance.

    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 ('Generate images') and specifies the resource ('using Volcengine's text-to-image API'), making the purpose immediately understandable. However, since there are no sibling tools mentioned, it doesn't need to distinguish from alternatives, so it can't achieve 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, prerequisites, or typical use cases. It simply states what the tool does without any contextual usage information.

    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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  • Evaluate tool definition quality.

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