Lucidity MCP

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# Lucidity MCP - Implementation Plan

This checklist outlines the steps to build and deploy Lucidity MCP using Python and the FastMCP SDK.

## Phase 1: Setup and Environment ✅

- [x] Create GitHub repository (`lucidity-mcp`)
- [x] Set up Python development environment
- [x] Install core dependencies:
  - [x] FastMCP SDK
  - [x] Testing frameworks (pytest)
  - [x] Documentation tools
- [x] Set up project structure following Python best practices
- [x] Create initial README with project description and setup instructions
- [ ] Set up GitHub Actions for CI/CD

## Phase 2: Core Implementation ✅

- [x] Define server configuration and metadata
  - [x] Server name, version, description
  - [x] Capability declarations
- [x] Implement the core MCP server using FastMCP
  - [x] Setup basic server skeleton
  - [x] Configure stdio transport
  - [x] Implement initialization logic

## Phase 3: Issue Definitions and Prompts ✅

- [x] Define the comprehensive catalog of code quality issues:
  - [x] Unnecessary complexity
  - [x] Poor abstractions
  - [x] Unintended code deletion
  - [x] Hallucinated components
  - [x] Style inconsistencies
  - [x] Security vulnerabilities
  - [x] Performance issues
  - [x] Code duplication
  - [x] Incomplete error handling
  - [x] Test coverage gaps
- [x] For each issue type, define:
  - [x] Clear name and description
  - [x] Detailed checkpoints for analysis
  - [x] Severity classification guidelines
- [x] Implement prompt generation logic
  - [x] Base prompt template with instructions and response format
  - [x] Language-specific adaptations
  - [x] Original vs. new code comparison handling
  - [x] Issue-specific prompt sections

## Phase 4: Tool Implementation ✅

- [x] Implement the `analyze_changes` tool
  - [x] Define input schema (code, original code, language, focus areas)
  - [x] Implement tool execution handler
  - [x] Generate structured analysis prompts
  - [x] Format and return results

## Phase 5: Testing 🔄

- [x] Implement unit tests for all components
  - [x] Core server functionality
  - [x] Prompt generation logic
  - [x] Tool implementation
- [ ] Create integration tests with mock MCP clients
- [ ] Develop a suite of example code samples for testing
  - [ ] Samples demonstrating each issue type
  - [ ] Multi-issue examples
  - [ ] Different programming languages
- [ ] Manual testing with Claude for Desktop
- [ ] Collect and analyze test results
- [ ] Refine implementation based on test findings

## Phase 6: Documentation 🔄

- [ ] Complete API documentation
- [ ] Create usage examples for different scenarios
- [x] Document installation and setup process
- [ ] Create troubleshooting guide
- [x] Implement inline code documentation
- [ ] Develop user guide with:
  - [ ] Setup instructions
  - [ ] Integration with different MCP clients
  - [ ] Example usage patterns
  - [ ] Customization options

## Phase 7: Refinement

- [ ] Optimize prompt generation
- [ ] Refine issue definitions based on testing
- [ ] Implement feedback mechanism for issue detection quality
- [ ] Add support for additional languages or language-specific checks
- [ ] Optimize performance for large codebases
- [ ] Implement caching if needed

## Phase 8: Deployment and Distribution

- [ ] Package for PyPI distribution
- [ ] Create deployment documentation
- [ ] Set up versioning strategy
- [ ] Create release notes for initial version
- [ ] Publish to PyPI
- [ ] Set up update mechanism

## Phase 9: Integration Examples

- [ ] Create integration examples with:
  - [ ] Claude for Desktop
  - [ ] VS Code via custom MCP client
  - [ ] CI/CD pipelines
- [ ] Document integration patterns

## Phase 10: Community and Support

- [ ] Set up issue templates on GitHub
- [ ] Create contribution guidelines
- [ ] Establish support channels
- [ ] Develop plan for ongoing maintenance
- [ ] Create community engagement strategy

## New Phase: SSE Transport Enhancement ✅

- [x] Implement SSE (Server-Sent Events) transport
  - [x] Create HTTP server for network-based MCP connections
  - [x] Configure CORS for API access
  - [x] Implement proper shutdown and error handling
- [x] Enhance logging system
  - [x] Support multiple logging modes (console, file, stderr)
  - [x] Add proper error handling and exception tracking
  - [x] Configure log levels appropriately for different components

## Future Enhancements (Post-MVP)

- [ ] Add customization options for prompts
- [ ] Implement persistent storage for analysis history
- [ ] Create visualization for code quality trends
- [ ] Develop language-specific analysis enhancements
- [ ] Implement project-level analysis capabilities
- [ ] Add multi-file analysis support
- [ ] Create plugin system for custom issue types