Lucidity Code Analyzer MCP Server

Developer ToolsPython

AI-powered code quality analysis for git changes

Available Tools

analyze_changes

Analyzes git changes for code quality issues across multiple dimensions

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get_changed_files

Retrieves a list of files that have been modified in the current git repository

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parse_git_diff

Parses git diff output to extract detailed information about code changes

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Lucidity is a powerful code analysis tool that helps AI assistants review code changes more effectively. By analyzing git diffs across multiple quality dimensions including complexity, security vulnerabilities, and error handling, Lucidity provides structured guidance for better code reviews. The tool is designed to work seamlessly with AI coding assistants through the Model Context Protocol (MCP), enabling them to provide more insightful and actionable feedback on code changes before they're committed. With its git-aware analysis capabilities, Lucidity is particularly valuable for pre-commit reviews and maintaining high code quality standards.

Overview

Lucidity is a Model Context Protocol (MCP) server designed to enhance the quality of AI-generated code through intelligent, prompt-based analysis. It helps identify and address common quality issues across 10 critical dimensions, resulting in cleaner, more maintainable, and more robust code.

Installation

To install Lucidity, follow these steps:

Clone the repository:

git clone https://github.com/hyperb1iss/lucidity-mcp.git
cd lucidity-mcp

Install the package using pip or uv:

# Using pip
pip install -e .

# Or using uv
uv install -e .

Configure your MCP client to use Lucidity by adding the appropriate configuration to your client settings.

Usage

Lucidity can be run in two transport modes:

Standard I/O Mode

For terminal-based interaction:

lucidity-mcp --transport stdio

Server-Sent Events (SSE) Mode

For network-based communication:

lucidity-mcp --transport sse --port 8000

Logging Options

Lucidity provides flexible logging options:

# Log to a file (useful for stdio transport)
lucidity-mcp --transport stdio --log-file lucidity.log

# Set log level
lucidity-mcp --log-level DEBUG

Working with AI Assistants

When using Lucidity with an AI assistant, you can ask questions like:

"Can you analyze the changes in my current git branch?"
"Review my code changes for security vulnerabilities"
"Check my recent commits for potential performance issues"
"Analyze the complexity of the changes I've made"

The AI assistant will use Lucidity to analyze your git changes and provide structured feedback on various quality dimensions.

Features

Lucidity analyzes code across multiple dimensions:

Complexity and readability
Security vulnerabilities
Error handling
Performance considerations
Maintainability
Testability
Documentation quality
Consistency with existing code
Potential bugs
Best practices adherence

The analysis is git-aware, focusing specifically on changes rather than entire codebases, making it ideal for pre-commit reviews and continuous integration workflows.