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DocuMind MCP Server

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🌐 DocuMind MCP 服务器

“当文档遇见数字智能”

下一代模型上下文协议 (MCP) 服务器通过先进的神经处理彻底改变了文档质量分析。

⚡ 核心系统

  • 🧠神经文档分析：用于全面评估 README 的高级算法

  • 🔮全息标题扫描：用于视觉元素的尖端 SVG 分析

  • 🌍多维语言支持：跨语言文档验证

  • 💫量子建议引擎：人工智能驱动的改进建议

Related MCP server: Lucidity MCP

🚀 系统启动顺序

系统要求

  • Node.js 18+

  • npm || yarn

初始化核心

npm install

编译矩阵

npm run build

神经发育链接

建立实时神经连接：

npm run watch

🛸 操作协议

系统配置

与 Claude Desktop 主机集成：

Windows 终端：

// %APPDATA%/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "documind-mcp-server": {
      "command": "/path/to/documind-mcp-server/build/index.js"
    }
  }
}

神经接口命令

评估自述文件

启动文档结构的量子分析。

参数：

  • projectPath ：到目标目录的神经通路

示例请求：

{
  name: "evaluate_readme",
  arguments: {
    projectPath: "/path/to/project"
  }
}

响应示例：

{
  content: [
    {
      type: "text",
      text: JSON.stringify({
        filePath: "/path/to/project/README.md",
        hasHeaderImage: true,
        headerImageQuality: {
          hasGradient: true,
          hasAnimation: true,
          // ... other quality metrics
        },
        score: 95,
        suggestions: [
          "Consider adding language badges",
          // ... other suggestions
        ]
      })
    }
  ]
}

🔮 发展矩阵

调试协议

通过 MCP Inspector 访问神经网络：

npm run inspector

故障排除指南

常见问题和解决方案

  1. 未检测到标题图像

    • 确保 SVG 文件放置在assets/目录中

    • 验证 SVG 文件是否包含正确的 XML 结构

    • 检查文件权限

  2. 语言标记无法识别

    • 验证徽章使用 shields.io 格式

    • 检查 HTML 结构是否遵循推荐的模式

    • 确保正确的中心对齐

  3. 构建错误

    • 清除node_modules并重新安装依赖项

    • 确保 TypeScript 版本符合项目要求

    • 检查修改后的文件中的语法错误

  4. MCP 连接问题

    • 验证 stdio 传输配置

    • 检查 Claude Desktop 配置

    • 确保配置中的文件路径正确

性能优化

  1. SVG分析

    • 最小化 SVG 复杂性以实现更快的解析

    • 使用高效的渐变和动画

    • 优化文件大小同时保持质量

  2. 自述文件扫描

    • 结构内容以实现最佳解析

    • 使用推荐的 Markdown 模式

    • 遵循徽章放置指南

🔬 API 文档

核心课程

自述服务

主要服务为README的分析与评估。

class ReadmeService {
  // Analyzes all README files in a project
  async evaluateAllReadmes(projectPath: string): Promise<ReadmeEvaluation[]>
  
  // Evaluates a single README file
  private async evaluateReadme(dirPath: string, readmePath: string): Promise<ReadmeEvaluation>
  
  // Evaluates language badge configuration
  private evaluateLanguageBadges(content: string): BadgeEvaluation
}

SVG服务

专门针对 SVG 标题图像分析的服务。

class SVGService {
  // Evaluates SVG header image quality
  public evaluateHeaderImageQuality(imgSrc: string, content: string): HeaderImageQuality
  
  // Checks for project-specific elements in SVG
  private checkProjectSpecificImage(svgContent: string, readmeContent: string): boolean
}

核心接口

interface ReadmeEvaluation {
  filePath: string;
  hasHeaderImage: boolean;
  headerImageQuality: HeaderImageQuality;
  isCentered: {
    headerImage: boolean;
    title: boolean;
    badges: boolean;
  };
  hasBadges: {
    english: boolean;
    japanese: boolean;
    isCentered: boolean;
    hasCorrectFormat: boolean;
  };
  score: number;
  suggestions: string[];
}

interface HeaderImageQuality {
  hasGradient: boolean;
  hasAnimation: boolean;
  hasRoundedCorners: boolean;
  hasEnglishText: boolean;
  isProjectSpecific: boolean;
}

错误处理

服务器实现了全面的错误处理：

try {
  const evaluations = await readmeService.evaluateAllReadmes(projectPath);
  // Process results
} catch (error) {
  const errorMessage = error instanceof Error ? error.message : String(error);
  return {
    content: [{
      type: 'text',
      text: `Evaluation error: ${errorMessage}`
    }],
    isError: true
  };
}

⚡ 许可证

根据 MIT 协议运行。

Available Tools

1 tool
evaluate_readmeC

リポジトリ内の全てのREADMEファイルの構成を評価し、改善点を提案します

ParametersJSON Schema
NameRequiredDescriptionDefault
projectPathYesプロジェクトのルートディレクトリパス

TDQS

C2.9/5.0
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 evaluation and proposal of improvements but does not specify how the evaluation is performed (e.g., criteria, depth), what format the proposals take, whether it modifies files or only reports, or any constraints like rate limits or permissions needed. 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 in Japanese that directly states the tool's function without unnecessary words. It is front-loaded with the core action and outcome, making it easy to parse. This minimal structure earns a top score for conciseness.

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 (evaluating and proposing improvements for README files) and the absence of annotations and output schema, the description is insufficient. It lacks details on evaluation criteria, output format, behavioral traits, and usage context. Without this information, an AI agent would struggle to understand the full scope and limitations of the 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 single parameter 'projectPath' clearly documented as 'プロジェクトのルートディレクトリパス' (project root directory path). The description does not add any additional meaning or context beyond what the schema provides, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately handles parameter semantics.

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: 'evaluate the structure of all README files in a repository and propose improvements.' It specifies the verb ('evaluate'), resource ('README files'), and outcome ('propose improvements'), making the intent unambiguous. However, since there are no sibling tools, it cannot demonstrate differentiation from alternatives, which prevents a perfect score.

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, prerequisites, or exclusions. It simply states what the tool does without context for its application. This lack of usage instructions limits its effectiveness for an AI agent in selecting the right tool for a scenario.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedevaluate_readme
Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

B3/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The tool has a single, clear purpose of evaluating README files in repositories.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The name 'evaluate_readme' follows a clear verb_noun pattern.

Tool Count2/5

One tool is too few for a server named 'DocuMind MCP Server', which suggests a broader documentation-related purpose. This feels thin and limited in scope, lacking coverage for other documentation tasks.

Completeness1/5

The server is severely incomplete for its implied domain of documentation management. It only handles README evaluation, missing obvious gaps like creating, updating, or analyzing other documentation types, or managing documentation workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

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