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hanoak

pixabay-mcp-server

by hanoak

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.1

  • Disambiguation5/5

    Each tool targets a unique combination of action (search/get) and resource type (image/video), so there is no overlap or ambiguity. An agent can easily distinguish pixabay_search_images from pixabay_get_image.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with a common prefix (pixabay_), using snake_case throughout. The convention is uniform and predictable.

    Tool Count5/5

    Four tools is an ideal scope for a media search-and-retrieve server, covering the essential operations without redundancy. Each tool serves a distinct purpose.

    Completeness5/5

    The tool surface fully covers the core lifecycle for a read-only media API: search both images and videos, then fetch full details by ID. No obvious missing operations are needed for the stated purpose.

  • Average 4.3/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 69 commits in the last 12 weeks
    • Last stable release on
    • 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.

  • 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.

  • This repository includes a glama.json configuration file.

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    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

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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

  • Behavior4/5

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

    With readOnlyHint and openWorldHint already in annotations, the description adds behavioral context by stating it returns a token-efficient summary (one representative URL plus metadata) and that get_image provides full size tiers. It does not disclose pagination counts or rate limits, but this is sufficient given the annotations.

    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?

    Two sentences, front-loaded with the primary action and resource, followed by output behavior and a redirect to a sibling tool. No filler or repetition.

    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?

    With 13 parameters and no output schema, the description clarifies the return format ('token-efficient summary', 'one representative image URL plus metadata') and points to pixabay_get_image for complete data. This is adequate for a search tool, though it could mention pagination behavior explicitly; the schema covers that via page/per_page.

    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 100%, so the baseline is 3. The description only mentions 'keyword and filters' generically, adding no specific parameter meaning beyond what the schema already provides. Parameters like safesearch, orientation, and colors are fully documented in the schema.

    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 uses a specific verb ('Search') and resource ('Pixabay's library of royalty-free images') with filters, clearly distinguishing from siblings. It also notes the token-efficient summary and follow-up call to pixabay_get_image, which differentiates it from the get and video search tools.

    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 explicitly directs users to pixabay_get_image for full size tiers, providing a follow-up alternative. It implies use for image search rather than video search through the title and sibling context, but does not explicitly state when not to use it versus pixabay_search_videos.

    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?

    Annotations already mark this as read-only, so the description's added detail about returning every size tier provides useful behavioral context beyond what annotations convey. It doesn't cover error cases or rate limits, but those are less critical given the read-only hint.

    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?

    Single sentence, front-loaded with the action and resource, no unnecessary words. Every word earns its place.

    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?

    For a simple one-parameter fetch tool with read-only annotations and no output schema, the description covers the essential behavior: fetching a single image and returning all size tiers. It is adequately complete.

    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 100%, and the description essentially restates that the id identifies the image. No new semantic detail is added, so baseline 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?

    Clearly states it fetches a single Pixabay image by id, distinguishing it from search tools (which list images) and the video sibling. The phrase 'including every size tier' adds specific scope not visible from the tool name.

    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?

    Gives concrete context by noting the id comes from pixabay_search_images, implying appropriate use after searching. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for a simple fetch tool.

    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?

    Annotations already declare read-only and open-world; the description adds that the response contains every size tier, providing useful behavioral context beyond what annotations offer.

    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?

    A single concise sentence that is front-loaded with the verb and resource, and adds relevant detail without unnecessary words.

    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?

    For a simple one-parameter read-only tool with clear annotations and no output schema, the description gives enough context about the return value (all size tiers) and usage context.

    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 is 100% covering the id parameter, and the description repeats the same information without adding new semantic meaning, warranting the baseline score.

    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 fetches a single video by ID, distinguishing it from search and image tools. It also specifies that all size tiers are included, making the scope precise.

    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 clearly indicates when to use (when you have an ID from pixabay_search_videos), but doesn't explicitly state when not to use or name alternatives, though sibling tools imply them.

    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?

    Beyond the readOnlyHint annotation, the description discloses that the tool returns a token-efficient summary with one representative video URL plus metadata, not the full size tiers. This adds valuable behavioral context about the output shape and resource efficiency.

    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 exactly two sentences, front-loaded with the core purpose followed by essential behavioral guidance. Every word adds value, with no redundancy or filler.

    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?

    For an 11-parameter search tool with rich schema annotations and readOnlyHint, the description explains the return format and directs to get_video for full details. It provides sufficient context for an agent to invoke the tool correctly even without an output schema.

    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 100% with detailed descriptions for all 11 parameters, so the description need not explain them individually. The generic mention of 'keyword and filters' adds no extra meaning beyond what the schema already provides.

    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 specifies the tool searches Pixabay's royalty-free video library by keyword and filters, using a specific verb and resource. It distinguishes itself from sibling tools like pixabay_get_video, which retrieves full video size tiers for a specific ID.

    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?

    It explicitly directs users to call pixabay_get_video with an id for the full set of size tiers after receiving the summary, providing an alternative for complete data retrieval. This establishes when to use this search tool versus the get companion.

    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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