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cola-sk

Figma Context MCP

by cola-sk
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.4

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion between tools. The single tool's purpose is clearly defined.

    Naming Consistency5/5

    The sole tool name 'convert-figma-to-code' follows a clear verb-noun pattern, and with only one tool, naming consistency is trivially maintained.

    Tool Count3/5

    The server has only one tool, which feels thin for a 'Figma Context' server. While the tool itself is focused, the count is on the borderline of being too few for typical usage.

    Completeness1/5

    The server only provides a single conversion tool, lacking any other Figma-related functionality (e.g., listing files, fetching styles, or managing components). This is severely incomplete for a server named 'Figma Context'.

  • Average 3.8/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 4 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

  • Behavior3/5

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

    No annotations are provided, so the description carries full burden. It discloses the required environment variable and the basic action (fetch, convert), but does not cover behavioral details like rate limits, output format specifics, error handling, or side effects. The description is adequate but not rich.

    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 short sentences, front-loaded with the main action and then the prerequisite. Every sentence is valuable with no wasted words.

    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?

    For a simple tool with one parameter and no output schema, the description covers the essential action and a key prerequisite. It could mention the output code language or format, but overall it is fairly complete given the low complexity.

    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?

    Input schema covers 100% of the single parameter with a clear description and example. The tool description adds the prerequisite but does not add additional meaning beyond the schema. 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?

    Description clearly states the tool fetches a Figma node and its rendered image, then converts to a code block. Verb and resource are specific, and no sibling tools exist to differentiate, so high clarity.

    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?

    Description mentions the prerequisite (FIGMA_ACCESS_TOKEN) but provides no guidance on when to use this tool versus alternatives, nor any when-not-to-use context. Since no siblings exist, the lack of differentiation is not critical, but usage guidance is minimal.

    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 the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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