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ilker-tosun

brave-image-mcp

by ilker-tosun
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation4/5

    The two tools are clearly differentiated by batch vs single query, and descriptions explicitly state this. However, since both are image searches, an agent might initially be unsure which to use without reading carefully.

    Naming Consistency5/5

    Both tools follow the same verb_noun pattern with a descriptive suffix ('batch' for the multi-query variant). The naming is consistent and predictable.

    Tool Count3/5

    With only two tools, the server feels thin for a general-purpose image search API. While the scope is narrow, a single search tool with a batch flag could have sufficed, making the current count borderline.

    Completeness4/5

    The core search capability is well covered, including a batch mode for multiple queries. Minor gaps exist, such as missing pagination or filtering options, but for an image search server the essential operations are present.

  • Average 3.7/5 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

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  • This repository includes a README.md file.

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

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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?

    With no annotations, the description carries full transparency burden. It discloses the output content (URLs, thumbnails, dimensions, source pages, metadata), which is useful. However, it does not explicitly state that the operation is read-only, nor does it mention any rate limits, restrictions, or other behavioral nuances, so it only partially fulfills the transparency requirement.

    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 two sentences, front-loaded with the core purpose, and contains no redundant wording. Every word contributes value, making it appropriately concise and well-structured.

    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?

    The description explains what the tool does and what it returns, which covers basic usage. However, it lacks any mention of the sibling batch tool, how they relate, or when to choose one over the other. Given the existence of 'search_images_batch', this is a notable gap in contextual completeness.

    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 input schema has 100% coverage with detailed descriptions for all six parameters. The tool description adds no additional parameter semantic information, so the baseline of 3 is appropriate.

    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 searches for images and lists the return data (URLs, thumbnails, dimensions, source pages, metadata). However, it does not distinguish this tool from its sibling 'search_images_batch', so it misses the full specificity of a 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 gives no guidance on when to use this tool versus the sibling 'search_images_batch'. There is no mention of alternatives or any situational context, leaving the agent without explicit usage direction.

    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?

    No annotations are provided, so the description carries the burden. It discloses that queries run sequentially and results are combined, which are meaningful behavioral traits. It does not discuss error handling or rate limits, but for a read-only search tool this is acceptable.

    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 two sentences, front-loaded with the main action, and contains no redundant or filler content.

    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?

    With no output schema and moderate complexity (6 params), the description explains the core behavior but leaves gaps around return format and partial-failure behavior when multiple queries are involved. The schema covers parameter details, but the tool description could more fully describe expected outputs.

    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%, with every parameter having a description. The tool description adds no parameter-level detail beyond what the schema already provides, so a 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 tool as searching for images using multiple queries in a single call, and explicitly distinguishes it from single-query search by emphasizing batch behavior and combined results.

    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?

    It states the tool is useful for collecting images across several topics at once, implying batch use. However, it does not explicitly mention when not to use it or directly compare with the sibling search_images tool.

    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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