DocuMind MCP Server
by MCP-Mirror
DocuMind MCP Server is a next-generation Model Context Protocol (MCP) server designed to revolutionize documentation quality analysis. It leverages advanced neural processing for comprehensive README evaluation and improvement recommendations.
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What is DocuMind MCP Server?
DocuMind MCP Server is a server that analyzes and evaluates the quality of documentation, particularly README files, using advanced neural processing techniques. It provides suggestions for improvement based on various metrics like header image quality, language badge presence, and overall structure.
How to use DocuMind MCP Server?
To use the server, you need Node.js 18+ and npm or yarn. First, install the dependencies using npm install. Then, compile the matrix with npm run build. Integrate the server with Claude Desktop by configuring the claude_desktop_config.json file with the path to the built index.js file. Finally, use the evaluate_readme command with the project path to initiate the analysis.
Key features of DocuMind MCP Server
Neural Documentation Analysis
Holographic Header Scanning
Multi-dimensional Language Support
Quantum Suggestion Engine
Use cases of DocuMind MCP Server
Improving README quality
Automated documentation review
Ensuring consistent documentation standards
Providing AI-powered documentation suggestions
FAQ from DocuMind MCP Server
Header Image Not Detected
Header Image Not Detected
Ensure SVG file is placed in the assets/ directory, contains proper XML structure, and check file permissions.
Language Badges Not Recognized
Language Badges Not Recognized
Verify badges use shields.io format, check HTML structure follows recommended pattern, and ensure proper center alignment.
Build Errors
Build Errors
Clear node_modules and reinstall dependencies, ensure TypeScript version matches project requirements, and check for syntax errors in modified files.
MCP Connection Issues
MCP Connection Issues
Verify stdio transport configuration, check Claude Desktop configuration, and ensure proper file paths in config.
How to optimize SVG Analysis?
How to optimize SVG Analysis?
Minimize SVG complexity for faster parsing, use efficient gradients and animations, and optimize file size while maintaining quality.