DocuMind MCP Server

DocuMind MCP Server

A Model Context Protocol server that analyzes and evaluates GitHub README documentation quality using advanced neural processing, providing scores and improvement suggestions.

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evaluate_readme

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

README

<div align="center"> <img src="assets/header.svg" alt="DocuMind MCP Server" width="800">

<div align="center"> <a href="README.md"><img src="https://img.shields.io/badge/english-document-blue.svg" alt="EN doc"></a> <a href="README.ja.md"><img src="https://img.shields.io/badge/ドキュメント-日本語-blue.svg" alt="JA doc"/></a> </div> </div>

🌐 DocuMind MCP Server

"Where Documentation Meets Digital Intelligence"

A next-generation Model Context Protocol (MCP) server that revolutionizes documentation quality analysis through advanced neural processing.

⚡ Core Systems

  • 🧠 Neural Documentation Analysis: Advanced algorithms for comprehensive README evaluation
  • 🔮 Holographic Header Scanning: Cutting-edge SVG analysis for visual elements
  • 🌍 Multi-dimensional Language Support: Cross-linguistic documentation verification
  • 💫 Quantum Suggestion Engine: AI-powered improvement recommendations

🚀 System Boot Sequence

System Requirements

  • Node.js 18+
  • npm || yarn

Initialize Core

npm install

Compile Matrix

npm run build

Neural Development Link

Establish real-time neural connection:

npm run watch

🛸 Operation Protocol

System Configuration

Integrate with Claude Desktop mainframe:

Windows Terminal:

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

Neural Interface Commands

evaluate_readme

Initiates quantum analysis of documentation structure.

Parameters:

  • projectPath: Neural pathway to target directory

Example Request:

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

Example Response:

{
  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
        ]
      })
    }
  ]
}

🔮 Development Matrix

Debug Protocol

Access the neural network through MCP Inspector:

npm run inspector

Troubleshooting Guide

Common Issues and Solutions

  1. Header Image Not Detected

    • Ensure SVG file is placed in the assets/ directory
    • Validate SVG file contains proper XML structure
    • Check file permissions
  2. Language Badges Not Recognized

    • Verify badges use shields.io format
    • Check HTML structure follows recommended pattern
    • Ensure proper center alignment
  3. Build Errors

    • Clear node_modules and reinstall dependencies
    • Ensure TypeScript version matches project requirements
    • Check for syntax errors in modified files
  4. MCP Connection Issues

    • Verify stdio transport configuration
    • Check Claude Desktop configuration
    • Ensure proper file paths in config

Performance Optimization

  1. SVG Analysis

    • Minimize SVG complexity for faster parsing
    • Use efficient gradients and animations
    • Optimize file size while maintaining quality
  2. README Scanning

    • Structure content for optimal parsing
    • Use recommended markdown patterns
    • Follow badge placement guidelines

🔬 API Documentation

Core Classes

ReadmeService

Primary service for README analysis and evaluation.

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
}

SVGService

Specialized service for SVG header image analysis.

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
}

Core Interfaces

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;
}

Error Handling

The server implements comprehensive error handling:

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
  };
}

⚡ License

Operating under MIT Protocol.

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