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mariokernich

imgflip-mcp

by mariokernich
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.1

  • Disambiguation5/5

    get_memes and caption_image have completely distinct purposes: one lists available templates, the other creates a meme from a template. There is no overlap or confusion between them.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern (get_memes, caption_image), making the API predictable and easy to navigate.

    Tool Count3/5

    With only 2 tools, the set feels minimal but not trivial. It covers the core workflow of finding a template and captioning it, though it's on the thin side for a dedicated meme service.

    Completeness5/5

    The domain is meme generation, and the two tools provide complete lifecycle coverage: discovering templates and creating the final meme. No obvious missing operations for the stated purpose.

  • Average 4.8/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 21 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.

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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

  • Behavior5/5

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

    The annotations already declare readOnlyHint and openWorldHint, but the description adds valuable context: the approximate count (~100), ordering by recent captioning frequency, the exact fields returned (id, name, URL, dimensions, box_count), and free/no-credentials requirement. This enriches the behavioral understanding beyond the structured 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?

    The description is two sentences, front-loaded with the core purpose, and then provides concise details about the output and auth. Every sentence earns its place with no redundancy or fluff.

    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 list tool with no output schema, the description fully explains what is returned, how it is ordered, and that it requires no credentials. It also connects to the sibling tool by highlighting the id's role, making it contextually 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?

    Both parameters (limit and name_filter) are fully described in the schema with descriptions and constraints. The tool description does not add extra parameter-specific semantics, but it does mention the default ordering and that the id is needed for captioning, which indirectly relates to usage. Given 100% schema coverage, 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 states the verb 'Get' and the resource 'popular Imgflip meme templates', with specific details about ordering and data fields. It distinguishes itself from the sibling tool 'caption_image' by explicitly noting the id is needed for captioning.

    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 clear context: it lists popular meme templates and notes they are needed for caption_image, implying a typical usage flow. However, it does not explicitly state when to use this tool over alternatives or mention any exclusions.

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

  • Behavior5/5

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

    The description adds valuable behavioral context beyond the annotations: it states the tool returns an inline image plus URL, requires IMGFLIP_USERNAME/IMGFLIP_PASSWORD credentials, and clarifies that boxes overrides text0/text1. These details help the agent anticipate side effects and prerequisites.

    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 compact yet information-dense, with a clear flow: primary use case, return value, prerequisite, parameter selection guidance, and authentication requirement. No filler or redundant repetition.

    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 tool with no output schema, the description sufficiently covers the return format (inline image + URL), the required setup (get_memes, credentials), and the key parameter strategies. This makes it complete for an agent to invoke the tool correctly in a realistic workflow.

    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?

    Although the schema covers 100% of parameters, the description enriches the semantic meaning by explaining that template_id comes from get_memes, text0 is top text, text1 is bottom text, and boxes is an alternative that takes precedence. This adds practical usage guidance beyond the raw 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 clearly states the tool creates a meme by captioning an Imgflip template, with a specific verb and resource. It distinguishes itself from the sibling tool get_memes by focusing on the captioning action rather than fetching templates.

    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 says to use this whenever the user asks for a meme rather than drawing one, and instructs to call get_memes first to obtain template_id and box_count. It also prescribes when to use text0/text1 versus the boxes array, including the precedence rule.

    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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