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ananddtyagi

GIF Creator MCP

by ananddtyagi
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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 ambiguity or overlap between tools. The tool's purpose is clearly defined as converting video to GIF, leaving no room for confusion or misselection.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency since there are no other tools to compare against. The tool name 'convert_video_to_gif' follows a clear verb_noun pattern, but consistency cannot be assessed across multiple tools.

    Tool Count2/5

    A single tool for a GIF creator server feels thin and incomplete for the domain. While the tool performs a core function, typical GIF creation workflows might include additional operations like resizing, cropping, adjusting speed, or creating GIFs from images, suggesting the scope is underdeveloped.

    Completeness2/5

    The tool set is severely incomplete for a GIF creator domain. It only covers video-to-GIF conversion, missing essential operations such as creating GIFs from image sequences, editing existing GIFs (e.g., trimming, optimizing), or managing output settings (e.g., frame rate, quality). This will likely cause agent failures when broader tasks are required.

  • Average 2.9/5 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

  • 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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output location but doesn't cover critical behaviors like whether the tool overwrites existing files, handles errors, requires specific permissions, or has performance constraints. For a file conversion tool with zero annotation coverage, this leaves significant 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?

    The description is a single, clear sentence that efficiently conveys the core functionality without unnecessary details. It's front-loaded with the main action and location, making it easy to understand at a glance.

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

    Completeness2/5

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

    Given the complexity of a video-to-GIF conversion tool with no annotations and no output schema, the description is incomplete. It lacks information about output format, error handling, file size considerations, and behavioral traits, which are essential for proper tool invocation.

    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 doesn't add any parameter-specific information beyond what's already in the schema, which has 100% coverage. It mentions the output directory but doesn't explain parameter interactions or defaults. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.

    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: converting a video file to a GIF file. It specifies the verb 'convert' and the resources involved (video to GIF), and mentions the output location ('in the same directory'). However, it doesn't differentiate from siblings since none exist, so it can't achieve a perfect score of 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. It doesn't mention prerequisites, limitations, or scenarios where other tools might be more appropriate. With no sibling tools, this isn't a major issue, but it still lacks explicit usage context.

    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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