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Sunwood-ai-labs_documind-MCP-Server
镜像://github.com/sunwood-ai-labs/documind-mcp-server
3 years
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🌐 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
-
Header Image Not Detected
- Ensure SVG file is placed in the
assets/
directory - Validate SVG file contains proper XML structure
- Check file permissions
- Ensure SVG file is placed in the
-
Language Badges Not Recognized
- Verify badges use shields.io format
- Check HTML structure follows recommended pattern
- Ensure proper center alignment
-
Build Errors
- Clear
node_modules
and reinstall dependencies - Ensure TypeScript version matches project requirements
- Check for syntax errors in modified files
- Clear
-
MCP Connection Issues
- Verify stdio transport configuration
- Check Claude Desktop configuration
- Ensure proper file paths in config
Performance Optimization
-
SVG Analysis
- Minimize SVG complexity for faster parsing
- Use efficient gradients and animations
- Optimize file size while maintaining quality
-
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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Reviews

user_lfhrfLtX
The Model Context Protocol (MCP) Server by RonTrace has significantly improved our project management efficiency. Its intuitive interface and robust performance are unparalleled. The seamless integration with various AI protocols has been a game-changer. Highly recommend for teams looking to streamline their workflows. Check it out at https://mcp.so/server/ai-rules-mcp/RonTrace.