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.

- 🧠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

Integrate with Claude Desktop mainframe:

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

Initiates quantum analysis of documentation structure.

- projectPath: Neural pathway to target directory

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

{ 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 ] }) } ] }

Access the neural network through MCP Inspector:

- Ensure SVG file is placed in theassets/directory
- Validate SVG file contains proper XML structure
- Check file permissions

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

- Clearnode_modulesand reinstall dependencies
- Ensure TypeScript version matches project requirements
- Check for syntax errors in modified files

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

- Minimize SVG complexity for faster parsing
- Use efficient gradients and animations
- Optimize file size while maintaining quality

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

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 }

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 }

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; }

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 }; }

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