# 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