Sunwood Ai Labs Documind MCP Server

🚀 DocuMind MCP Server

"The intersection of documentation and digital intelligence"

A revolutionary Model Context Protocol (MCP) server that transforms document quality analysis through advanced neural processing.

🚀 Quick Start

System Requirements

• Node.js 18+
• npm || yarn

Initialize the Core

npm install

Compile the Matrix

npm run build

Neural Development Link

Establish a real-time neural connection:

npm run watch

✨ Features

• 🧠 Neural Document Analysis: Advanced algorithms for comprehensive README evaluation.
• 🔮 Holographic Title Scanning: Cutting-edge SVG analysis for visual elements.
• 🌍 Multidimensional Language Support: Cross - language document validation.
• 💫 Quantum Suggestion Engine: AI - driven improvement suggestions.

💻 Usage Examples

System Configuration

Integrate with the Claude Desktop host:

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

Initiate quantum analysis of the document structure.

Parameters:

• projectPath: Neural pathway to the 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 indicators...
        },
        score: 95,
        suggestions: [
          "Consider adding language badges",
          // Other suggestions...
        ]
      })
    }
  ]
}

🔧 Technical Details

Debugging Protocol

Access the neural network through the MCP inspector:

npm run inspector

Troubleshooting Guide

Common Issues and Solutions

1. Title image not detected

   • Ensure the SVG file is located in the assets/ directory.
   • Verify that the SVG file contains the correct XML structure.
   • Check file permissions.

2. Language badges not recognized

   • Confirm that the badges use the shields.io format.
   • Check if the HTML structure conforms to the recommended pattern.
   • Ensure proper centering alignment.

3. Build errors

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

4. MCP connection issues

   • Verify the stdio transmission configuration.
   • Check the Claude Desktop configuration.
   • Ensure the correct path is specified in the configuration.

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 the content for optimal parsing.
   • Ensure the title image, title, and badges are centered.

Error Handling

The server implements comprehensive error handling:

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

📄 License

This project is licensed under the MIT License.