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junmer

LottieFiles MCP Server

by junmer
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TypeScript
Remote

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: get_animation_details retrieves metadata for a specific animation, get_popular_animations lists trending animations, and search_animations enables keyword-based discovery. There is no overlap in functionality, making tool selection straightforward.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case (get_animation_details, get_popular_animations, search_animations). The naming is predictable and enhances readability across the set.

    Tool Count3/5

    With only 3 tools, the server feels thin for a Lottie animation platform. While the tools cover basic retrieval and search, the absence of creation, update, or management operations suggests limited scope, though it may be intentional for a read-only interface.

    Completeness2/5

    The toolset is severely incomplete for a typical animation platform, lacking any CRUD operations (e.g., upload_animation, update_animation, delete_animation) or interaction features (e.g., like_animation, download_animation). Agents can only retrieve and search, which may lead to dead ends in workflows requiring modification.

  • Average 3.1/5 across 3 of 3 tools scored.

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

    • 0 of 1 community issues answered or closed 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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    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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. It mentions 'Supports pagination', which adds some behavioral context beyond the input schema. However, it lacks details on authentication needs, rate limits, error handling, or what the search results look like (e.g., format, fields). For a search tool with zero annotation coverage, 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is two concise sentences with zero waste: the first states the purpose and criteria, the second adds pagination support. It's front-loaded and appropriately sized, with every sentence earning its place.

    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 no annotations, no output schema, and a search tool with 3 parameters, the description is incomplete. It doesn't explain what the search returns (e.g., list of animations with IDs/names), potential constraints like rate limits, or how to handle errors. This leaves significant gaps for an agent to use the tool effectively.

    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% description coverage, with clear docs for 'query', 'page', and 'limit'. The description adds minimal value by mentioning 'keywords, tags, and other criteria' which loosely relates to the 'query' parameter, but doesn't provide additional syntax or format details. Baseline 3 is appropriate as the schema does the heavy lifting.

    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 Lottie animations by keywords, tags, and other criteria.' It specifies the verb ('Search') and resource ('Lottie animations'), but doesn't explicitly differentiate from siblings like 'get_popular_animations' which might retrieve animations without search criteria. This makes it clear but not fully sibling-aware.

    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 like 'get_popular_animations' or 'get_animation_details'. It mentions 'Supports pagination' which hints at usage for large result sets, but lacks explicit when/when-not scenarios or prerequisites, leaving the agent to infer context.

    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 states the tool retrieves information, implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, or details the return format (e.g., JSON structure). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

    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, well-structured sentence that efficiently conveys the tool's purpose and scope without unnecessary words. It is front-loaded with the core action and includes relevant details (animation data, preview images, tags), making it highly concise and effective.

    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?

    Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, or output format. Without annotations or an output schema, more guidance would be beneficial, but it meets the minimum for a simple lookup tool.

    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% description coverage, with the 'id' parameter clearly documented as a 'Unique identifier of the animation'. The description adds no additional meaning beyond this, such as format examples or sourcing hints. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.

    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 with a specific verb ('Get') and resource ('detailed information about a specific Lottie animation'), including what information is retrieved (animation data, preview images, tags). It doesn't explicitly differentiate from siblings like 'get_popular_animations' or 'search_animations', but the focus on a 'specific' animation implies it's for individual lookup rather than listing or searching.

    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 like 'get_popular_animations' or 'search_animations'. It mentions a 'specific' animation, which hints at usage for known IDs, but lacks explicit when/when-not instructions or prerequisites, such as needing an animation ID from another source.

    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 retrieving a list but doesn't describe key behaviors such as how 'popular' is determined (e.g., by views, likes, recency), whether the list is cached or real-time, any rate limits, authentication needs, or what the return format looks like (e.g., JSON array of animation objects). For a read operation with no annotation coverage, this leaves significant gaps in understanding the tool's behavior.

    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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action ('Get a list') and resource ('currently popular Lottie animations'), making it easy to parse. There's no redundancy or fluff, and every part of the sentence contributes essential information.

    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 tool's complexity (a read operation with pagination), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like how popularity is defined, potential rate limits, or the structure of returned data. While the schema handles parameters well, the overall context for effective use by an AI agent is insufficient, as key operational details are missing.

    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% description coverage, with clear documentation for 'page' and 'limit' parameters including defaults and constraints. The description doesn't add any semantic details beyond what the schema provides, such as explaining how pagination affects the 'popular' list or typical use cases for adjusting limits. Since schema coverage is high, the baseline score of 3 is appropriate, 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 with a specific verb ('Get') and resource ('list of currently popular Lottie animations'). It distinguishes from the sibling 'get_animation_details' by focusing on popular animations rather than details, and from 'search_animations' by retrieving a curated list rather than performing a search. However, it doesn't explicitly mention the pagination aspect, which is part of the functionality.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies usage for retrieving popular animations, suggesting it should be used when a user wants trending or curated content rather than specific details or custom searches. It doesn't provide explicit when-not-to-use guidance or name alternatives, but the context of 'popular' vs. 'search' and 'details' gives some implied differentiation. No prerequisites or exclusions are mentioned.

    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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