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codingthefuturewithai

MCP Mermaid Image Gen

by codingthefuturewithai
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

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

  • Latest release: v0.1.4

  • Disambiguation5/5

    Each tool has a distinct output method: file persistence vs. base64 streaming. No ambiguity between them.

    Naming Consistency5/5

    Both tools follow the same verb_noun pattern 'generate_mermaid_diagram_' with a suffix differentiating output type ('file' vs 'stream').

    Tool Count4/5

    Only 2 tools, but they cover the two primary output modes for a focused diagram generation server. Slightly thin but reasonable.

    Completeness4/5

    Core functionality of generating Mermaid diagrams as images is covered via file and stream. Lacks SVG-specific handling or validation tools, but these are minor gaps.

  • Average 4.4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    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

  • Behavior3/5

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

    No annotations provided, so description carries full burden. It covers transport modes, prerequisites, and response format. However, it does not disclose behaviors like overwriting files, error handling if folder is missing, or side effects.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

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

    Well-structured with clear sections (purpose, prerequisites, parameter guidance, response, use case). Slightly lengthy but each section adds value. Front-loaded with primary purpose.

    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 no output schema and 6 parameters, description provides thorough guidance on parameters, prerequisites, and use cases. Lacks error handling details and examples, but is largely complete for typical usage.

    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?

    Schema coverage is 0%, but description's PARAMETER GUIDANCE section provides detailed explanations for all 6 parameters, including options for theme, format inference, and background color. This adds significant value beyond the bare 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 specific verb 'generate' and resource 'Mermaid diagram' and the action of saving to file system. It distinguishes from the sibling tool 'generate_mermaid_diagram_stream' by focusing on file persistence.

    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 a USE CASE section with explicit scenarios (client needs to persist to disk, has local FS access, needs file path). It also includes SYSTEM PREREQUISITES and ACCESS REQUIREMENTS. However, it does not explicitly state when not to use this tool vs the sibling stream tool.

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

  • Behavior4/5

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

    With no annotations, the description provides extensive behavioral details: system prerequisites, transport constraints, no file system access, and direct base64 streaming. However, it lacks specifics about error handling or behavior when prerequisites are not met.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

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

    The description is well-structured with clear sections and front-loaded purpose. While somewhat verbose, the level of detail is justified given the tool's complexity (streaming, prerequisites, transport). Could be slightly more concise but remains effective.

    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?

    The description covers system prerequisites, parameter usage, response format, and use cases, which is comprehensive for a tool with 4 parameters and no output schema. It could mention potential errors or limitations, but overall it provides sufficient context for an agent to decide to invoke the tool.

    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?

    The input schema has 0% description coverage, but the description compensates fully by explaining each parameter's purpose, allowed values for theme, formatting guidance for backgroundColor and format, and default behaviors. This adds significant value beyond the 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's purpose: generate a Mermaid diagram and return it as a base64-encoded image. It distinguishes from the sibling tool 'generate_mermaid_diagram_file' by emphasizing streaming and no file persistence.

    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?

    The description provides explicit when-to-use and when-not-to-use guidance, including system prerequisites, transport requirements (SSE only), and a dedicated 'USE CASE' section. It implicitly contrasts with the sibling tool for file-based persistence.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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