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wwwzhouhui

Mermaid MCP Server

by wwwzhouhui

get_supported_options

Retrieve available customization options for Mermaid diagrams, including themes and export formats, to configure visual output.

Instructions

获取转换器支持的选项,如图表主题和输出格式。

返回:
    一个包含支持的主题和格式列表的字典。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'get_supported_options' tool. It is decorated with @mcp.tool() for registration and directly returns the supported themes and formats as a dictionary.
    @mcp.tool()
    def get_supported_options() -> Dict[str, Any]:
        """
        获取转换器支持的选项,如图表主题和输出格式。
        
        返回:
            一个包含支持的主题和格式列表的字典。
        """
        logger.info("Providing list of supported options.")
        return {
            "themes": ["default", "dark", "neutral", "forest"],
            "formats": ["png", "jpg", "svg", "pdf"]
        }
Behavior3/5

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 discloses that the tool returns a dictionary with lists of supported themes and formats, which adds behavioral context beyond the input schema (which has no parameters). However, it doesn't cover other traits like performance, error handling, or authentication needs, leaving gaps in transparency for a tool with no annotation support.

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 highly concise and well-structured: two sentences that directly state the purpose and return value, with no wasted words. It's front-loaded with the core function, and every sentence adds essential information, making it efficient for an agent to parse.

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 low complexity (0 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains what the tool does and the return format, which complements the output schema. However, it lacks usage context and some behavioral details, preventing a perfect score despite the structured support.

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 tool has 0 parameters, and the input schema description coverage is 100% (with an empty schema). The description doesn't need to add parameter semantics, so it appropriately focuses on the return value. Since there are no parameters to document, a baseline score of 4 is justified, as the description doesn't introduce confusion or redundancy.

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: '获取转换器支持的选项,如图表主题和输出格式' (Get converter-supported options, such as chart themes and output formats). It specifies both the action ('获取' - get) and the resource ('支持的选项' - supported options), with concrete examples. However, it doesn't explicitly differentiate from sibling tools like 'convert_mermaid_to_image' or 'validate_mermaid_syntax', which prevents a 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 sibling tools or suggest scenarios where this tool is appropriate (e.g., before conversion to check available options). Without any usage context or exclusions, it relies on implicit understanding, which is insufficient for clear agent decision-making.

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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