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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a distinct purpose: searching stock photos, downloading with conversion, and optimizing local images. There is no overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (search_images, download_image, optimize_local_image), making them predictable.

    Tool Count5/5

    With 3 tools, the server is well-scoped for basic image bank operations: search, download, and optimize. The count is appropriate and not excessive.

    Completeness4/5

    The core workflow (search, download, optimize) is covered. Minor gaps exist, such as no tool for listing or deleting downloaded images, but these do not hinder the primary use case.

  • Average 4.4/5 across 3 of 3 tools scored. Lowest: 3.9/5.

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

    • No community issues in the last 6 months
    • 1 commit in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • 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

  • Behavior3/5

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

    No annotations are provided, so the description carries the burden. It discloses the conversion pipeline (EXIF rotation, resize, quality), which adds behavioral context. However, it does not mention potential side effects like overwrite behavior (default false), file size limits, or error handling, leaving some gaps.

    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?

    Three sentences, each essential: defines function, gives usage context, states constraint. No fluff. Information is front-loaded and clear.

    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 the absence of output schema and annotations, the description covers purpose, usage, and input constraint. However, it omits details about return value (e.g., success/path), error conditions, and behavior of parameters like overwrite. This is adequate but leaves the agent needing to infer some behavior.

    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 coverage is 50% (3 of 6 parameters have descriptions). The description adds context about the pipeline (quality, max-width) but does not elaborate on individual parameter semantics beyond what the schema already provides. Baseline 3 is appropriate; it doesn't significantly enhance parameter understanding.

    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 it converts a local image to WebP using a specific pipeline (EXIF rotation, max-width resize, quality control). It distinguishes from siblings by mentioning the same pipeline as download_image and a specific use case (replacing stock photos).

    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 explicit when-to-use guidance ('Use it when replacing stock photos...') and a key constraint ('Input must be a file inside the project directory'). This helps the agent decide context, though it doesn't explicitly mention when not to use it or contrast with search_images.

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

  • Behavior4/5

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

    With no annotations, the description carries full burden. It discloses that the tool searches multiple providers, returns specific fields (preview URL, download URL, dimensions, author, attribution link), and warns against hotlinking. However, it does not mention rate limits, authentication requirements, or any side effects, which would make it fully 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 paragraph but packs essential information without redundancy. It is concise and front-loaded with the main purpose, though it could be slightly more structured (e.g., bullet points for return fields).

    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?

    No output schema exists, so the description must cover return values, which it does by listing preview URL, download URL, dimensions, author, and attribution link. It also explains the workflow with the sibling tool. For a search tool, this is fairly complete, though it lacks details on pagination or error handling.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds value by explaining how to use the download URL (pass to download_image) and mentions that English queries yield better results and that color filter support varies by provider, going beyond the schema definitions.

    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 it searches free stock photos on Pexels, Unsplash, and Pixabay. It distinguishes from the sibling tool download_image by specifying that search results should be passed to that tool for placing images. The purpose is specific and unambiguous.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explicitly states when to use this tool ('when the project needs a real photo and the client has NOT provided their own images') and when not to ('Prefer client-provided photos when they exist'). It also gives a tip about English queries and directs the agent to use download_image for placing images, which is excellent guidance.

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

  • Behavior4/5

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

    Without annotations, the description covers key behaviors: conversion to WebP, optional resizing, default output directory, overwrite parameter, and the Unsplash requirement. It does not explicitly mention side effects like network requests or file system writes, but these are implied. A higher score would require explicit mention of non-destructiveness or rate limits.

    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 concise and well-structured. It opens with the main action and result, then adds important constraints and guidelines. Every sentence adds value without redundancy.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

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

    Given no output schema, the description explains the return value (relative path for <Image src>). It covers all major aspects: source URLs, conversion, resizing, quality, naming, and overwrite behavior. The tool's purpose and usage are thoroughly described for an 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?

    Schema description coverage is 100%, so baseline is 3. The description adds value beyond the schema: clarifies the filename should be kebab-case, maxWidth resizes down only, outputDir default is public/images, and trackDownloadUrl is required for Unsplash. This provides useful context.

    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 tool downloads an image, converts it to WebP, optionally resizes it, saves it in the project, and returns a relative path. It distinguishes from siblings by specifying it works with URLs from search_images and mentions the accepted sources.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly states when to use the tool: after search_images, and only for URLs from pexels.com, unsplash.com, and pixabay.com. Also specifies that trackDownloadUrl must be passed for Unsplash results, providing clear prerequisites.

    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 the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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