ACE MCP Server

# Progress Tracking: ACE MCP Server ## Current Sprint: Initialization & LLM Provider Implementation **Sprint Start**: 2025-10-28 **Sprint Goal**: Initialize project, implement LLM provider abstraction, configure Docker **Status**: 20% Complete --- ## Progress Overview ``` Phase 1: Project Analysis & Setup [████████████████████] 100% Phase 2: LLM Provider Abstraction [░░░░░░░░░░░░░░░░░░░░] 0% Phase 3: Configuration Management [░░░░░░░░░░░░░░░░░░░░] 0% Phase 4: Docker Configuration [░░░░░░░░░░░░░░░░░░░░] 0% Phase 5: Testing & Validation [░░░░░░░░░░░░░░░░░░░░] 0% Phase 6: Documentation [░░░░░░░░░░░░░░░░░░░░] 0% Phase 7: Deployment Testing [░░░░░░░░░░░░░░░░░░░░] 0% ``` **Overall Progress**: 20% (Phase 1 complete) --- ## Completed Work ### 2025-10-28: Memory Bank Initialization ✅ **Time**: ~1 hour **Focus**: VAN Mode - Project initialization and context building #### Created Files 1. ✅ `memory-bank/projectbrief.md` - Project overview and objectives - Technology stack - Success criteria - Research foundation 2. ✅ `memory-bank/techContext.md` - Technology stack details - ACE framework components - LLM provider abstraction design - Docker architecture - File structure 3. ✅ `memory-bank/productContext.md` - Product vision - Target users - Key features (including new requirements) - Use cases - Value propositions 4. ✅ `memory-bank/systemPatterns.md` - Architectural patterns - Design patterns - Error handling patterns - Docker patterns - Testing patterns - Best practices 5. ✅ `memory-bank/activeContext.md` - Current task tracking - Key decisions - Open questions - Risk assessment 6. ✅ `memory-bank/tasks.md` - Detailed implementation roadmap - 7 phases with checklists - Timeline estimates - Completion criteria 7. ✅ `memory-bank/progress.md` (this file) - Progress tracking - Completed work - Next actions #### Project Analysis - ✅ Verified project structure exists - ✅ Confirmed package.json and tsconfig.json present - ✅ Dashboard files identified (HTML/JS/CSS) - ✅ Identified missing TypeScript source files - ✅ Analyzed LM Studio API endpoints - ✅ Created directory structure for Memory Bank #### Key Decisions Made 1. **LLM Provider Architecture**: Strategy pattern with factory method 2. **Docker Strategy**: Multi-container with Docker Compose 3. **Configuration**: Environment variables with Zod validation --- ## In Progress ### Current Task: Phase 1.2 - Project Structure Analysis **Status**: Ready to start **Next Steps**: 1. Create `style-guide.md` 2. Review existing `package.json` dependencies 3. Analyze `tsconfig.json` configuration 4. List all missing TypeScript source files --- ## Upcoming Work ### Next Session: Phase 2 - LLM Provider Implementation **Estimated Time**: 3 hours **Priority**: P0 **Components to Implement**: 1. `src/llm/provider.ts` - Core interface 2. `src/llm/openai.ts` - OpenAI implementation 3. `src/llm/lmstudio.ts` - LM Studio implementation 4. `src/llm/factory.ts` - Provider factory **Dependencies to Install**: - `openai` - OpenAI SDK - `axios` - HTTP client for LM Studio --- ## Blockers & Issues ### Current Blockers None at this time. ### Resolved Issues 1. ✅ **Memory Bank Location**: Confirmed to use `/memory-bank/` directory 2. ✅ **Project Scope**: Clarified need for dual deployment (local + VM) 3. ✅ **LLM Requirements**: Identified both OpenAI and LM Studio support needed ### Open Questions 1. **MCP Transport in Docker**: How to handle stdio transport with containerized server? - Research needed: stdio vs HTTP transport options - May need to document both approaches 2. **Dashboard API Connection**: How does dashboard communicate with MCP server? - Current dashboard is standalone demo - May need API proxy or WebSocket bridge --- ## Metrics ### Code Metrics - **Lines of Code**: 0 (TypeScript not yet implemented) - **Test Coverage**: 0% (no tests yet) - **Documentation Pages**: 7 (Memory Bank) ### Time Metrics - **Time Spent**: 1 hour - **Estimated Remaining**: 13 hours - **On Track**: Yes ### Quality Metrics - **Memory Bank Completeness**: 100% - **Project Understanding**: High - **Architecture Clarity**: High --- ## Risk Status ### Technical Risks | Risk | Severity | Status | Mitigation | |------|----------|--------|------------| | MCP stdio in Docker | Medium | Open | Document both stdio and HTTP transport | | LM Studio API differences | Low | Open | Test thoroughly, add adapter layer | | TypeScript files missing | High | Known | Will implement in Phase 2+ | | Dashboard Docker networking | Low | Open | Use named networks, document setup | ### Schedule Risks | Risk | Severity | Status | Mitigation | |------|----------|--------|------------| | Underestimated complexity | Low | Monitoring | Incremental approach, regular updates | | Dependency issues | Low | Monitoring | Use exact versions in package.json | | Testing time | Medium | Open | Parallel test development | --- ## Next Actions (Prioritized) ### Immediate (Next 30 mins) 1. 🎯 Create `style-guide.md` 2. 🎯 Review `package.json` and list dependencies 3. 🎯 Check if TypeScript source files exist (likely missing) ### Short-term (Next 2 hours) 1. 🎯 Start Phase 2: Implement LLM provider interface 2. 🎯 Implement OpenAI provider 3. 🎯 Implement LM Studio provider ### Medium-term (Next 4 hours) 1. 🎯 Phase 3: Configuration management 2. 🎯 Phase 4: Docker configuration 3. 🎯 Test local Docker deployment --- ## Success Indicators ### Phase 1 Success ✅ - [x] Memory Bank completely populated - [x] Project structure understood - [x] Key decisions documented - [x] Implementation roadmap created ### Phase 2 Success (Pending) - [ ] LLM provider interface defined - [ ] OpenAI provider working - [ ] LM Studio provider working - [ ] Tests passing ### Overall Project Success (Pending) - [ ] Can switch between OpenAI and LM Studio via config - [ ] Docker Compose starts all services - [ ] Dashboard accessible - [ ] MCP server connects to Cursor AI - [ ] Full ACE workflow works with both providers --- ## Communication Log ### 2025-10-28 08:00 - User Request User requested: 1. Initialize project based on DESCRIPTION.md 2. Read structure and documentation 3. Create Memory Bank 4. Prepare for development tasks 5. Add Docker support (local + Ubuntu VM) 6. Add LLM provider switching (OpenAI + LM Studio) **Response**: Initiated VAN mode, created comprehensive Memory Bank --- ## Notes - User communicates in Russian - Code and documentation in English - LM Studio server: http://10.242.247.136:11888/v1 - Both local and remote deployment equally important - User expects auto-continuation without asking permission --- ## Version History | Version | Date | Changes | |---------|------|---------| | 1.0 | 2025-10-28 | Initial progress tracking created | --- **Last Updated**: 2025-10-28 **Updated By**: VAN Mode Initialization **Next Review**: After completing Phase 1.2