9 months ago
developer-toolsAI-powered code quality analysis using MCP to help AI assistants review code more effectively. Analyze git changes for complexity, security issues, and more through structured prompts.
Overview
What is Lucidity MCP?
Lucidity MCP is an AI-powered code quality analysis tool that utilizes the Model Context Protocol (MCP) to help AI assistants review code more effectively by analyzing git changes for complexity, security issues, and more through structured prompts.
How to use Lucidity MCP?
To use Lucidity MCP, clone the repository, set up a virtual environment, install dependencies, and run the server. Connect your AI assistant using the MCP protocol URI to analyze code quality feedback.
Key features of Lucidity MCP?
- Comprehensive issue detection across 10 critical quality dimensions.
- Contextual analysis comparing changes against original code.
- Language agnostic, supporting any programming language.
- Focused analysis targeting specific issue types.
- Structured outputs providing actionable feedback.
- Seamless integration with MCP-compatible AI assistants.
- Lightweight implementation with minimal dependencies.
- Extensible framework for adding new issue types.
- Git-aware analysis for pre-commit reviews.
Use cases of Lucidity MCP?
- Analyzing code quality in git changes before committing.
- Checking for security vulnerabilities in code.
- Ensuring adherence to coding standards and best practices.
- Identifying performance issues and code duplication.
- Improving code abstractions and error handling.
FAQ from Lucidity MCP?
- Can Lucidity MCP analyze any programming language?
Yes! It is designed to work with any language the AI assistant understands.
- Is Lucidity MCP free to use?
Yes! It is open-source and free for everyone.
- How does Lucidity MCP ensure code quality?
It analyzes code across multiple dimensions, providing detailed feedback and recommendations.