mcp-adr-analysis-server

# Documentation Update Plan: Research-Driven Architecture ## Overview This plan outlines the documentation updates needed to communicate the new research-driven architecture direction for the MCP ADR Analysis Server. ## Priority: HIGH 🔴 The research-driven architecture is a **major paradigm shift** from traditional RAG approaches and needs comprehensive documentation. --- ## Phase 1: Core Documentation (Week 1) ### 1.1 Main README.md Updates **File**: ../../README.md` **Changes Needed**: 1. **Add Research-Driven Section** (after "Features") ```markdown ## Research-Driven Architecture Unlike traditional RAG systems, this MCP server answers questions by querying **live environment resources**: - 📁 **Project Files** (configs, code, ADRs) - 🧠 **Knowledge Graph** (ADR relationships) - 🔧 **Environment Resources** (Kubernetes, Docker, OS metrics) - 🌐 **Web Search** (fallback only) **Why Not RAG?** Your infrastructure changes constantly. Live queries ensure accuracy. [Learn more →](./notes/RESEARCH-DRIVEN-ARCHITECTURE.md) ``` 2. **Update Tool List** (add `perform_research`) ```markdown ### New: Research Tools - `perform_research` - Answer questions using cascading sources - `generate_research_questions` - Generate context-aware research questions ``` 3. **Add Red Hat Section** ```markdown ## Red Hat Support First-class support for Red Hat ecosystem: - ✅ OpenShift (`oc` CLI) - ✅ Podman (containers & pods) - ✅ Ansible (inventories, playbooks) Auto-detects available tools and provides live data. ``` 4. **Update Quick Start** (add research example) ````markdown ## Quick Start ### Perform Research Ask questions about your project using live data: ```json { "tool": "perform_research", "args": { "question": "What container orchestration are we using?" } } ``` ```` The server cascades through project files → knowledge graph → environment → web search. ``` ``` **Priority**: 🔴 **CRITICAL** - Users need to understand the new paradigm **Estimated Time**: 2 hours --- ### 1.2 Architecture Documentation **File**: `/./ARCHITECTURE.md` (NEW or update existing) **Content Structure**: ```markdown # Architecture Overview ## Research-Driven Design ### Cascading Source Hierarchy [Diagram showing the cascade] ### Component Architecture - ResearchOrchestrator - EnvironmentCapabilityRegistry - Knowledge Graph Integration ### Why Not RAG? - Real-time data vs stale documents - Lower maintenance overhead - Perfect for infrastructure decisions ``` **Priority**: 🟡 **HIGH** - Important for technical understanding **Estimated Time**: 3 hours --- ### 1.3 API Documentation Updates **File**: `/./API.md` or `/./TOOLS.md` **Changes Needed**: 1. Add `perform_research` tool documentation 2. Update `generate_research_questions` with new capabilities 3. Add environment capability examples **Example Entry**: ````markdown ## perform_research Answer research questions using cascading sources. ### Input Schema ```json { "question": string, // Required: Research question "projectPath": string, // Optional: Project path "confidenceThreshold": number // Optional: 0-1, default 0.6 } ``` ```` ### Example ```json { "tool": "perform_research", "args": { "question": "What deployment strategy do we use?", "confidenceThreshold": 0.7 } } ``` ### Response Returns: - Sources consulted (project files, knowledge graph, environment) - Confidence score - Synthesized answer - Web search recommendation (if needed) ```` **Priority**: 🟡 **HIGH** **Estimated Time**: 2 hours --- ## Phase 2: Integration Guides (Week 2) ### 2.1 Red Hat Integration Guide **File**: `/./RED-HAT-INTEGRATION.md` (NEW) **Content**: ```markdown # Red Hat Integration Guide ## Supported Tools ### OpenShift - Installation requirements - Configuration - Example queries - Common patterns ### Podman - Podman vs Docker differences - Pod management - Example queries ### Ansible - Inventory setup - Playbook discovery - Integration patterns ## Auto-Detection How the system detects Red Hat tools... ## Configuration Environment variables and settings... ## Examples Real-world usage examples... ## Troubleshooting Common issues and solutions... ```` **Priority**: 🟢 **MEDIUM** - Important for Red Hat users **Estimated Time**: 4 hours --- ### 2.2 Environment Setup Guide **File**: `/./ENVIRONMENT-SETUP.md` (NEW) **Content**: ```markdown # Environment Setup Guide ## Overview The MCP server auto-detects environment capabilities. ## Supported Environments ### Kubernetes - kubectl installation - Context configuration - Permissions needed ### Docker/Podman - Installation - Socket permissions - Rootless configuration ### Operating System - Supported platforms - Required permissions ## Verification How to verify capabilities are detected... ## Troubleshooting Common detection issues... ``` **Priority**: 🟢 **MEDIUM** **Estimated Time**: 3 hours --- ## Phase 3: Tutorial Content (Week 3) ### 3.1 Research Workflow Tutorial **File**: `/./tutorials/RESEARCH-WORKFLOW.md` (NEW) **Content**: ```markdown # Research Workflow Tutorial ## Introduction Learn how to use the research-driven architecture... ## Scenario 1: Discovering Container Setup Step-by-step guide... ## Scenario 2: Investigating Deployment Strategy Step-by-step guide... ## Scenario 3: OpenShift Route Analysis Step-by-step guide... ## Advanced: Custom Research Patterns How to structure complex research questions... ``` **Priority**: 🟢 **MEDIUM** **Estimated Time**: 4 hours --- ### 3.2 Migration Guide (RAG to Research-Driven) **File**: `/./MIGRATION-FROM-RAG.md` (NEW) **Content**: ```markdown # Migrating from RAG to Research-Driven ## Why Migrate? Benefits of research-driven over RAG... ## Conceptual Differences | RAG | Research-Driven | | --- | --------------- | | ... | ... | ## Migration Steps 1. Remove vector database dependencies 2. Configure environment tools 3. Update queries 4. Test cascading sources ## Examples Before (RAG): ... After (Research): ... ``` **Priority**: 🔵 **LOW** - Nice to have **Estimated Time**: 2 hours --- ## Phase 4: Video & Visual Content (Week 4) ### 4.1 Architecture Diagrams **Files**: Various `.png` or `.svg` in `/./diagrams/` **Needed Diagrams**: 1. Cascading source hierarchy (flow diagram) 2. Component architecture (system diagram) 3. Environment capability detection (sequence diagram) 4. Research flow with confidence scores (decision tree) **Tools**: Mermaid, draw.io, or Excalidraw **Priority**: 🟢 **MEDIUM** **Estimated Time**: 6 hours --- ### 4.2 Demo Video/GIF **File**: `demo.gif` or link to video **Content**: - Show research query execution - Demonstrate environment detection - Show confidence scoring - Illustrate web search fallback **Priority**: 🔵 **LOW** - Great for engagement **Estimated Time**: 4 hours --- ## Phase 5: Blog Posts & Announcements (Ongoing) ### 5.1 Announcement Blog Post **Platform**: GitHub Discussions, Medium, Dev.to **Content**: ```markdown # Introducing Research-Driven Architecture for MCP Servers Why we moved away from RAG... How it works... Benefits for smaller LLMs... Try it yourself... ``` **Priority**: 🟢 **MEDIUM** **Estimated Time**: 3 hours --- ### 5.2 Technical Deep Dive **Platform**: Blog or documentation site **Content**: - Implementation details - Performance benchmarks - Comparison with RAG - Future roadmap **Priority**: 🔵 **LOW** **Estimated Time**: 5 hours --- ## Summary: Documentation Deliverables ### Critical (Phase 1) - [ ] Update README.md with research-driven section - [ ] Add Red Hat support section - [ ] Update tool list - [ ] Create ARCHITECTURE.md - [ ] Update API documentation ### High Priority (Phase 2) - [ ] Create RED-HAT-INTEGRATION.md - [ ] Create ENVIRONMENT-SETUP.md - [ ] Add troubleshooting guides ### Medium Priority (Phase 3) - [ ] Create tutorial content - [ ] Add architecture diagrams - [ ] Create example projects ### Nice to Have (Phase 4+) - [ ] Migration guide from RAG - [ ] Demo videos/GIFs - [ ] Blog posts - [ ] Technical deep dives --- ## Estimated Total Time - **Phase 1** (Critical): 7 hours - **Phase 2** (High): 7 hours - **Phase 3** (Medium): 6 hours - **Phase 4** (Low): 10 hours - **Phase 5** (Ongoing): 8 hours **Total**: ~38 hours (1 week full-time) --- ## Success Metrics ### Documentation Quality - [ ] All new tools documented - [ ] Examples for each capability - [ ] Troubleshooting sections complete - [ ] Architecture clearly explained ### User Understanding - [ ] Users understand RAG vs Research-Driven - [ ] Red Hat users can set up easily - [ ] Clear migration path provided - [ ] Confidence scoring explained ### Community Engagement - [ ] GitHub stars increase - [ ] Issues/questions about features decrease - [ ] Positive feedback on new direction - [ ] External blog posts/mentions --- ## Maintenance Plan ### Regular Updates (Monthly) - [ ] Update capability list as new tools are added - [ ] Add community-contributed examples - [ ] Refresh troubleshooting with new issues - [ ] Update performance benchmarks ### Version Updates (Per Release) - [ ] Update API schemas - [ ] Add new tool documentation - [ ] Update compatibility matrix - [ ] Refresh examples --- ## Review & Approval Process 1. **Draft** → Technical review by maintainers 2. **Review** → User testing & feedback 3. **Revise** → Incorporate feedback 4. **Publish** → Deploy to documentation site 5. **Announce** → Share in community channels --- ## Questions to Address in Documentation Users will likely ask: 1. **"Why not use RAG?"** → Answer in README and ARCHITECTURE.md 2. **"How do I install Red Hat tools?"** → RED-HAT-INTEGRATION.md 3. **"What if tools aren't detected?"** → ENVIRONMENT-SETUP.md + troubleshooting 4. **"Can I use this without environment tools?"** → Yes, project files + knowledge graph 5. **"How accurate is this vs RAG?"** → Benchmarks in blog post 6. **"What happens when confidence is low?"** → API docs + examples 7. **"Does this work with small LLMs?"** → Benefits section in README --- ## Next Steps (Immediate) 1. ✅ Create this plan document 2. 🔴 **Update README.md** (highest priority) 3. 🔴 **Create ARCHITECTURE.md** 4. 🟡 **Update API documentation** 5. 🟡 **Create RED-HAT-INTEGRATION.md** **Owner**: Documentation team / maintainers **Timeline**: Start immediately, complete Phase 1 in 1 week