# Active Context - MCP Atlassian Server
## Current Mode
**VAN Mode** - ✅ COMPLETED
## Completed Assessment
**Complexity Level**: Level 2 (Simple Enhancement)
**Next Phase**: IMPLEMENT Mode for code quality improvements
## Project State
- Memory Bank system: ✅ Initialized
- Project structure: ✅ Analyzed
- Core files: ✅ Created
- VAN assessment: ✅ Completed
## Key Findings
1. **Project Type**: MCP server for Atlassian integration
2. **Technology**: Python-based, MCP protocol compliant
3. **Scope**: Confluence and Jira integration with AI models
4. **Status**: Production-ready with comprehensive testing
5. **Code Quality**: 627 linting issues identified (mostly style/formatting)
## Complexity Assessment
- **Codebase**: Large (78 source files, 18,576 lines)
- **Testing**: Extensive (88 test files, 1,014 test cases, all passing)
- **Architecture**: Well-structured, modular design
- **Issues**: Code quality/style improvements needed
## Immediate Focus
**Code Quality Enhancement**:
- 390 line-too-long issues (E501)
- 99 blind-except issues (BLE001)
- 71 f-string-in-exception issues (EM102)
- 47 boolean argument issues (FBT001/FBT002)
- 20 other minor issues
## Environment
- Platform: macOS (darwin 24.5.0)
- Shell: /bin/zsh
- Python: 3.13.5 (virtual environment)
- Workspace: /Users/arsenikonakhau/Desktop/_DEVELOPER_/MCP/mcp-server--atlassian
## Next Steps
1. Transition to IMPLEMENT mode
2. Address code quality issues systematically
3. Maintain test coverage and functionality
4. Document improvements
