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helloHupc

Pixabay MCP Server

by helloHupc
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

67%
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: one searches for images and the other searches for videos. There is no overlap in functionality, and the descriptions explicitly differentiate between media types, making it impossible for an agent to confuse them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'search_' prefix followed by the media type (images/videos). The naming is perfectly uniform and predictable across the tool set.

    Tool Count2/5

    With only two tools, this server feels thin for a media search service. While search is core, there are obvious gaps like fetching specific media by ID, getting trending content, or managing downloads. The count is too low for comprehensive coverage of the Pixabay domain.

    Completeness2/5

    The tool surface is severely incomplete for a Pixabay API server. It only provides search functionality, missing essential operations like retrieving specific images/videos by ID, getting user uploads, or accessing categories/trends. Agents will hit dead ends when trying to perform basic media retrieval tasks beyond searching.

  • Average 3.4/5 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

  • 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 the tool searches for videos and returns results with URLs/metadata, but doesn't describe rate limits, authentication requirements, pagination behavior beyond parameters, error conditions, or what constitutes a successful search. The description is minimal and lacks important operational context.

    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 perfectly structured and concise. It starts with the core purpose, then provides a cleanly formatted parameter section with clear explanations, and ends with return value information. Every sentence earns its place with no wasted words or redundant information.

    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?

    Given the tool has an output schema (which handles return values), the description provides good context for a search tool. It covers all parameters thoroughly and states the basic purpose. However, it lacks important behavioral context like rate limits, authentication needs, or error handling that would be valuable for an AI 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?

    The description provides excellent parameter semantics despite 0% schema description coverage. It explains what each parameter does with clear examples and constraints: 'query: Search term (e.g., "nature", "city")', 'per_page: Number of results per page (3-200)', and lists all valid values for video_type and category. This fully compensates for the lack of schema descriptions.

    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's purpose: 'Search for videos on Pixabay.' It specifies the resource (videos) and platform (Pixabay), but doesn't explicitly differentiate from its sibling tool 'search_images' beyond the resource type. The purpose is clear but lacks explicit sibling comparison.

    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. It doesn't mention the sibling tool 'search_images' or explain when to search for videos versus images. There's no context about use cases, prerequisites, or limitations beyond basic parameter descriptions.

    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. It mentions that the tool 'Search for images on Pixabay' and returns 'Search results with image URLs and metadata,' which implies a read-only operation but lacks details on permissions, rate limits, pagination behavior, or error handling. For a tool with 8 parameters and no annotations, this is insufficient.

    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 well-structured and appropriately sized, with a clear purpose statement followed by detailed parameter explanations and a returns section. Every sentence adds value, but it could be more front-loaded by emphasizing the tool's core function before listing parameters. However, it avoids redundancy and is efficiently organized.

    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?

    Given the tool's complexity (8 parameters, no annotations, but with an output schema), the description is mostly complete. It thoroughly documents parameters and states the return format, and the output schema likely covers return values, reducing the need for detailed output explanations. However, it lacks behavioral context like rate limits or authentication needs, which are important for a search tool.

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

    Parameters5/5

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

    The description adds significant meaning beyond the input schema, which has 0% schema description coverage. It explains each parameter's purpose with examples and constraints (e.g., 'query: Search term (e.g., "yellow flowers", "cat")', 'per_page: Number of results per page (3-200)'), compensating fully for the schema's lack of descriptions. This is essential for understanding how to use the parameters correctly.

    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's purpose: 'Search for images on Pixabay.' It specifies the verb ('search') and resource ('images on Pixabay'), making the action and target explicit. However, it does not differentiate from its sibling tool 'search_videos' (which searches videos on Pixabay), so it lacks sibling differentiation.

    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. It does not mention the sibling tool 'search_videos' or any other tools, nor does it specify contexts or exclusions for usage. The only implied usage is for searching images, but no explicit alternatives or constraints are provided.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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