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Patryk Ciechanski
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# Memory Bank (optional - can be committed for shared context)
memory-bank
# memory-bank

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# Active Context
This file tracks the project's current status, including recent changes, current goals, and open questions.
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## Current Focus
Documentation restructuring and Memory Bank framework implementation. Recently completed:
- Complete docs/ directory structure following CLAUDE.md guidelines
- GitHub issue/PR templates
- Docker user guide corrections
- Memory Bank initialization rules in CLAUDE.md
## Recent Changes
- Fixed Docker documentation to reflect automated Redis setup
- Created comprehensive user guides (installation, configuration, troubleshooting)
- Added development setup guide for contributors
- Implemented Memory Bank initialization protocols
- Added CLAUDE.md auto-refresh rules for context compaction
## Open Questions/Issues
- Testing the complete Memory Bank workflow
- Potential creation of remaining documentation files (architecture/, api/tools/)
- Validation of GitHub templates functionality
- Integration testing of documentation with actual setup process
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# Decision Log
This file records architectural and implementation decisions using a list format.
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## Decision
**Documentation Structure**: Follow CLAUDE.md specified directory structure exactly
**Rationale**: User emphasized importance of following CLAUDE.md structure rather than creating custom organization
**Implementation Details**: Created docs/{user-guides,contributing,architecture,api} structure with specified files
**Docker Documentation Approach**: Emphasize automated Redis setup rather than manual configuration
**Rationale**: Analysis revealed Redis is fully automated through docker-compose.yml, previous docs were incorrect
**Implementation Details**: Rewrote installation guide to highlight "Everything is handled automatically - no manual Redis setup required!"
**Memory Bank Integration**: Implement file-based Memory Bank alongside Memory MCP server
**Rationale**: Dual-system approach for maximum context preservation and cross-session continuity
**Implementation Details**: Created initialization protocols, update triggers, and UMB command for comprehensive memory management
**GitHub Templates Strategy**: Create comprehensive templates matching CONTRIBUTING.md patterns
**Rationale**: Professional repository needs structured issue/PR workflows for contributors
**Implementation Details**: 4 YAML issue templates + markdown PR template with validation requirements
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# Product Context
This file provides a high-level overview of the project and the expected product that will be created. Initially it is based upon projectBrief.md (if provided) and all other available project-related information in the working directory. This file is intended to be updated as the project evolves, and should be used to inform all other modes of the project's goals and context.
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## Project Goal
The Gemini MCP Server is a Model Context Protocol (MCP) server that provides Claude with access to Google's Gemini AI models through specialized tools. This enables sophisticated AI-assisted development workflows combining Claude's general capabilities with Gemini's deep analytical and creative thinking abilities.
## Key Features
- **Multiple specialized tools**: chat, thinkdeep, codereview, debug, analyze, precommit
- **Docker-based deployment** with automated Redis for conversation threading
- **Comprehensive documentation structure** for both technical and non-technical users
- **GitHub integration** with issue/PR templates
- **Memory Bank strategy** for long-term context preservation
- **Cross-tool collaboration** between Claude and Gemini
## Overall Architecture
MCP server architecture with:
- Individual tool implementations in `tools/` directory
- Shared utilities for file handling, git operations, token management
- Redis-based conversation memory for context preservation
- Docker Compose orchestration for easy deployment
- Comprehensive test suite for quality assurance
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# Progress
This file tracks the project's progress using a task list format.
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## Completed Tasks
- ✅ Create complete docs directory structure according to CLAUDE.md guidelines
- ✅ Move docker-user-guide.md to proper location in user-guides/
- ✅ Create GitHub issue templates (bug_report.yml, feature_request.yml, tool_addition.yml, documentation.yml)
- ✅ Create GitHub pull request template
- ✅ Fix Docker documentation to reflect automated Redis setup
- ✅ Create user guides: installation.md, configuration.md, troubleshooting.md
- ✅ Create development setup guide for contributors
- ✅ Add Memory Bank initialization rules to CLAUDE.md
- ✅ Add CLAUDE.md auto-refresh rules for context compaction
- ✅ Initialize Memory Bank with core files
## Current Tasks
- 🔄 Memory Bank is now ACTIVE and tracking project context
## Next Steps
- Consider creating remaining documentation files:
- docs/architecture/overview.md
- docs/api/tools/ documentation for individual Gemini tools
- docs/contributing/workflows.md, code-style.md, testing.md
- Test GitHub templates functionality
- Validate complete documentation setup process
- Consider committing changes to feature branch
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# System Patterns *Optional*
This file documents recurring patterns and standards used in the project.
It is optional, but recommended to be updated as the project evolves.
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## Coding Patterns
- **MCP Tool Structure**: Individual tools in `tools/` directory inherit from BaseTool
- **Configuration Management**: Centralized config.py with environment variable handling
- **Utility Organization**: Shared utilities in `utils/` for file operations, git, tokens
- **Testing Strategy**: Comprehensive test suite with both unit tests and live integration tests
## Architectural Patterns
- **Docker Compose Orchestration**: Multi-service setup with Redis for conversation memory
- **Memory Management**: Dual approach - file-based Memory Bank + Memory MCP entities
- **Documentation-Driven Development**: All code changes require corresponding documentation
- **Collaboration Framework**: Structured Claude-Gemini interaction patterns with tool selection matrix
## Testing Patterns
- **Separation of Concerns**: Unit tests (no API key) vs live integration tests (API key required)
- **Mocking Strategy**: Mock external API calls in unit tests to avoid rate limits
- **Quality Gates**: Pre-commit validation with multiple tools (codereview, precommit, etc.)
- **Environment Isolation**: Docker-based testing to ensure consistent environments
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