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documind-mcp-server

Analyzes and enhances the quality of documentation, specifically README files, by providing insights and suggestions for improvement. Utilizes advanced neural processing techniques for thorough evaluation and visual analysis of documentation elements.

Author

documind-mcp-server logo

Sunwood-ai-labs

No License

Quick Info

GitHub GitHub Stars 0
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Tools 1
Last Updated 2026-02-19

Tags

documentationdocumindanalyzesquality documentationdocumentation elementsdocumind mcp
EN doc JA doc

🌐 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

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
  2. Ensure SVG file is placed in the assets/ directory
  3. Validate SVG file contains proper XML structure
  4. Check file permissions

  5. Language Badges Not Recognized

  6. Verify badges use shields.io format
  7. Check HTML structure follows recommended pattern
  8. Ensure proper center alignment

  9. Build Errors

  10. Clear node_modules and reinstall dependencies
  11. Ensure TypeScript version matches project requirements
  12. Check for syntax errors in modified files

  13. MCP Connection Issues

  14. Verify stdio transport configuration
  15. Check Claude Desktop configuration
  16. Ensure proper file paths in config

Performance Optimization

  1. SVG Analysis
  2. Minimize SVG complexity for faster parsing
  3. Use efficient gradients and animations
  4. Optimize file size while maintaining quality

  5. README Scanning

  6. Structure content for optimal parsing
  7. Use recommended markdown patterns
  8. 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.

See Also

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