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Sunwood-ai-labs

DocuMind MCP Server

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🌐 DocuMind MCP 서버

"문서와 디지털 인텔리전스가 만나는 곳"

고급 신경망 처리를 통해 문서 품질 분석에 혁명을 일으키는 차세대 모델 컨텍스트 프로토콜(MCP) 서버입니다.

⚡ 핵심 시스템

  • 🧠 신경망 문서 분석 : 포괄적인 README 평가를 위한 고급 알고리즘

  • 🔮 홀로그램 헤더 스캐닝 : 시각적 요소에 대한 최첨단 SVG 분석

  • 🌍 다차원 언어 지원 : 언어 간 문서 검증

  • 💫 양자 제안 엔진 : AI 기반 개선 권장 사항

Related MCP server: Lucidity MCP

🚀 시스템 부팅 시퀀스

시스템 요구 사항

  • 노드.js 18+

  • npm || 얀

코어 초기화

지엑스피1

컴파일 매트릭스

npm run build

신경 발달 링크

실시간 신경 연결 설정:

npm run watch

🛸 운영 프로토콜

시스템 구성

Claude Desktop 메인프레임과 통합:

윈도우 터미널 :

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

신경 인터페이스 명령

평가_리드미

문서 구조의 양자 분석을 시작합니다.

매개변수:

  • projectPath : 대상 디렉토리로의 신경 경로

요청 예시:

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

응답 예시:

{
  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
        ]
      })
    }
  ]
}

🔮 개발 매트릭스

디버그 프로토콜

MCP Inspector를 통해 신경망에 액세스하세요.

npm run inspector

문제 해결 가이드

일반적인 문제 및 솔루션

  1. 헤더 이미지가 감지되지 않았습니다

    • SVG 파일이 assets/ 디렉토리에 있는지 확인하세요.

    • SVG 파일에 적절한 XML 구조가 포함되어 있는지 확인하세요.

    • 파일 권한 확인

  2. 언어 배지가 인식되지 않음

    • 배지가 shields.io 형식을 사용하는지 확인하세요

    • HTML 구조가 권장 패턴을 따르는지 확인하세요.

    • 적절한 중앙 정렬을 확인하세요

  3. 빌드 오류

    • node_modules 지우고 종속성을 다시 설치하세요

    • TypeScript 버전이 프로젝트 요구 사항과 일치하는지 확인하세요.

    • 수정된 파일의 구문 오류를 확인하세요

  4. MCP 연결 문제

    • stdio 전송 구성 확인

    • Claude Desktop 구성 확인

    • 구성에서 적절한 파일 경로를 확인하세요

성능 최적화

  1. SVG 분석

    • 더 빠른 구문 분석을 위해 SVG 복잡성을 최소화합니다.

    • 효율적인 그라디언트와 애니메이션을 사용하세요

    • 품질을 유지하면서 파일 크기를 최적화하세요

  2. README 스캐닝

    • 최적의 구문 분석을 위한 구조 콘텐츠

    • 권장되는 마크다운 패턴을 사용하세요

    • 배지 배치 지침을 따르세요

🔬 API 문서

핵심 수업

ReadmeService

README 분석 및 평가를 위한 기본 서비스입니다.

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
}

SVG서비스

SVG 헤더 이미지 분석을 위한 전문 서비스입니다.

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
}

핵심 인터페이스

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;
}

오류 처리

서버는 포괄적인 오류 처리를 구현합니다.

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
  };
}

⚡ 라이센스

MIT 프로토콜에 따라 운영됩니다.

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. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.0
    • First observedevaluate_readme
Install Server
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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

Resources

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