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DocuMCP Implementation Research Questions

Generated: January 14, 2025
Project: DocuMCP - Intelligent MCP Server for GitHub Pages Documentation Deployment
Phase: Pre-Implementation Research
Context: Comprehensive validation of ADR decisions and implementation planning

Research Overview​

This document contains systematic research questions organized by architectural domain, based on the 6 ADRs established for DocuMCP. Each section includes priority ratings, validation criteria, and expected outcomes to guide effective pre-implementation research.

Research Objectives​

  1. Validate technical feasibility of ADR decisions
  2. Identify implementation risks and mitigation strategies
  3. Research best practices for MCP server development
  4. Investigate SSG ecosystem integration patterns
  5. Explore Diataxis framework implementation approaches

Research Constraints​

  • TypeScript/Node.js ecosystem limitations
  • MCP specification compliance requirements
  • GitHub Pages deployment constraints
  • Performance and scalability requirements

Domain 1: MCP Server Architecture Research (ADR-001)​

Priority: HIGH - Foundation Critical​

Core Architecture Questions​

Q1.1: TypeScript MCP SDK Performance Characteristics

  • Question: What are the performance benchmarks and limitations of the TypeScript MCP SDK under heavy concurrent usage?
  • Priority: CRITICAL
  • Research Method: Performance testing, benchmark analysis
  • Success Criteria: Documented performance profiles for different load scenarios
  • Timeline: Week 1
  • Dependencies: None

Q1.2: Node.js Memory Management for Repository Analysis

  • Question: How can we optimize Node.js memory usage when analyzing large repositories (>10GB)?
  • Priority: HIGH
  • Research Method: Memory profiling, stress testing
  • Success Criteria: Memory optimization strategies with <2GB footprint for 10GB repos
  • Timeline: Week 1-2
  • Dependencies: Q1.1

Q1.3: MCP Tool Orchestration Patterns

  • Question: What are the most effective patterns for orchestrating complex multi-tool workflows in MCP?
  • Priority: HIGH
  • Research Method: Pattern analysis, prototype development
  • Success Criteria: Documented orchestration patterns with examples
  • Timeline: Week 2
  • Dependencies: Q1.1

Q1.4: Stateless Session Context Management

  • Question: How can we efficiently maintain temporary context across tool calls while preserving stateless architecture?
  • Priority: MEDIUM
  • Research Method: Architecture research, implementation prototyping
  • Success Criteria: Context management strategy that doesn't violate MCP principles
  • Timeline: Week 2-3
  • Dependencies: Q1.3

Q1.5: Error Recovery and Fault Tolerance

  • Question: What are the best practices for implementing robust error recovery in MCP servers?
  • Priority: HIGH
  • Research Method: Error pattern analysis, resilience testing
  • Success Criteria: Comprehensive error handling framework
  • Timeline: Week 3
  • Dependencies: Q1.1, Q1.3

Integration and Deployment Questions​

Q1.6: GitHub Copilot Integration Patterns

  • Question: What are the optimal integration patterns for MCP servers with GitHub Copilot?
  • Priority: MEDIUM
  • Research Method: Integration testing, user experience research
  • Success Criteria: Documented integration best practices
  • Timeline: Week 3-4
  • Dependencies: Q1.3

Q1.7: Development Environment Setup

  • Question: What tooling and development practices optimize TypeScript MCP server development?
  • Priority: LOW
  • Research Method: Tool evaluation, workflow analysis
  • Success Criteria: Development environment recommendations
  • Timeline: Week 4
  • Dependencies: None

Domain 2: Repository Analysis Engine Research (ADR-002)​

Priority: HIGH - Intelligence Foundation​

Analysis Algorithm Questions​

Q2.1: Multi-layered Analysis Performance

  • Question: How can we optimize the performance of parallel multi-layered repository analysis?
  • Priority: CRITICAL
  • Research Method: Algorithm optimization, parallel processing research
  • Success Criteria: Analysis completion <30 seconds for typical repositories
  • Timeline: Week 1-2
  • Dependencies: Q1.2

Q2.2: Language Ecosystem Detection Accuracy

  • Question: What are the most reliable methods for detecting and analyzing language ecosystems in repositories?
  • Priority: HIGH
  • Research Method: Accuracy testing across diverse repositories
  • Success Criteria: >95% accuracy for major language ecosystems
  • Timeline: Week 2
  • Dependencies: None

Q2.3: Content Analysis Natural Language Processing

  • Question: What NLP techniques are most effective for analyzing documentation quality and gaps?
  • Priority: MEDIUM
  • Research Method: NLP library evaluation, accuracy testing
  • Success Criteria: Reliable content quality assessment methodology
  • Timeline: Week 3
  • Dependencies: Q2.1

Q2.4: Complexity Scoring Algorithm Validation

  • Question: How can we validate and calibrate the project complexity scoring algorithm?
  • Priority: MEDIUM
  • Research Method: Validation against known project types, expert review
  • Success Criteria: Complexity scores correlate with manual expert assessment
  • Timeline: Week 3-4
  • Dependencies: Q2.1, Q2.2

Q2.5: Incremental Analysis Capabilities

  • Question: How can we implement incremental analysis for repositories that change over time?
  • Priority: LOW
  • Research Method: Differential analysis research, caching strategies
  • Success Criteria: Incremental analysis reduces re-analysis time by >80%
  • Timeline: Week 4+
  • Dependencies: Q2.1

Scalability and Performance Questions​

Q2.6: Large Repository Handling

  • Question: What strategies ensure reliable analysis of enterprise-scale repositories (>100GB)?
  • Priority: MEDIUM
  • Research Method: Scalability testing, streaming analysis research
  • Success Criteria: Successful analysis of repositories up to 100GB
  • Timeline: Week 2-3
  • Dependencies: Q1.2, Q2.1

Q2.7: Analysis Caching Strategies

  • Question: What caching strategies provide optimal performance for repository analysis?
  • Priority: MEDIUM
  • Research Method: Caching pattern research, performance testing
  • Success Criteria: Cache hit rates >70% for repeated analysis
  • Timeline: Week 3
  • Dependencies: Q2.1

Domain 3: SSG Recommendation Engine Research (ADR-003)​

Priority: HIGH - Core Intelligence​

Decision Analysis Questions​

Q3.1: Multi-Criteria Decision Algorithm Validation

  • Question: How can we validate the accuracy of the MCDA framework for SSG recommendations?
  • Priority: CRITICAL
  • Research Method: Validation against expert recommendations, A/B testing
  • Success Criteria: Algorithm recommendations match expert choices >85% of the time
  • Timeline: Week 1-2
  • Dependencies: Q2.4

Q3.2: SSG Capability Profiling Methodology

  • Question: What methodology ensures accurate and up-to-date SSG capability profiles?
  • Priority: HIGH
  • Research Method: SSG feature analysis, performance benchmarking
  • Success Criteria: Comprehensive profiles for 5 major SSGs
  • Timeline: Week 2-3
  • Dependencies: None

Q3.3: Confidence Score Calibration

  • Question: How can we calibrate confidence scores to accurately reflect recommendation reliability?
  • Priority: HIGH
  • Research Method: Statistical analysis, outcome tracking
  • Success Criteria: Confidence scores correlate with actual recommendation success
  • Timeline: Week 3
  • Dependencies: Q3.1

Q3.4: Performance Modeling Accuracy

  • Question: How accurate are our build time and performance predictions for different SSGs?
  • Priority: MEDIUM
  • Research Method: Prediction validation, real-world testing
  • Success Criteria: Performance predictions within 20% of actual results
  • Timeline: Week 3-4
  • Dependencies: Q3.2

Q3.5: Dynamic Weight Adjustment

  • Question: Should recommendation weights be dynamically adjusted based on project characteristics?
  • Priority: LOW
  • Research Method: Machine learning research, adaptive algorithm development
  • Success Criteria: Dynamic weighting improves recommendation accuracy by >10%
  • Timeline: Week 4+
  • Dependencies: Q3.1, Q3.3

Knowledge Base Maintenance Questions​

Q3.6: Automated SSG Capability Monitoring

  • Question: How can we automate the monitoring and updating of SSG capabilities?
  • Priority: MEDIUM
  • Research Method: API research, automation tool development
  • Success Criteria: Automated detection of SSG capability changes
  • Timeline: Week 4
  • Dependencies: Q3.2

Q3.7: Community Feedback Integration

  • Question: How can we integrate community feedback to improve recommendation accuracy?
  • Priority: LOW
  • Research Method: Feedback system design, data analysis methods
  • Success Criteria: Community feedback improves recommendations measurably
  • Timeline: Week 4+
  • Dependencies: Q3.1

Domain 4: Diataxis Framework Integration Research (ADR-004)​

Priority: MEDIUM - Quality Enhancement​

Implementation Strategy Questions​

Q4.1: Automated Content Structure Generation

  • Question: What are the most effective approaches for automating Diataxis-compliant structure generation?
  • Priority: HIGH
  • Research Method: Template system research, automation testing
  • Success Criteria: Automated generation of compliant structures for all supported SSGs
  • Timeline: Week 2
  • Dependencies: Q3.2

Q4.2: Content Planning Intelligence

  • Question: How can we intelligently suggest content based on project analysis and Diataxis principles?
  • Priority: MEDIUM
  • Research Method: Content analysis algorithms, suggestion accuracy testing
  • Success Criteria: Content suggestions deemed useful by documentation experts >80% of time
  • Timeline: Week 3
  • Dependencies: Q2.3, Q4.1

Q4.3: SSG-Specific Diataxis Adaptations

  • Question: How should Diataxis implementation be adapted for each SSG's unique capabilities?
  • Priority: MEDIUM
  • Research Method: SSG feature analysis, adaptation strategy development
  • Success Criteria: Optimal Diataxis implementation for each supported SSG
  • Timeline: Week 3-4
  • Dependencies: Q3.2, Q4.1

Q4.4: Navigation Generation Algorithms

  • Question: What algorithms generate the most intuitive navigation for Diataxis-organized content?
  • Priority: MEDIUM
  • Research Method: UX research, navigation pattern analysis
  • Success Criteria: Navigation usability scores >90% in user testing
  • Timeline: Week 4
  • Dependencies: Q4.1, Q4.3

Quality Assurance Questions​

Q4.5: Diataxis Compliance Validation

  • Question: How can we automatically validate Diataxis compliance in generated structures?
  • Priority: MEDIUM
  • Research Method: Validation algorithm development, compliance testing
  • Success Criteria: Automated compliance checking with >95% accuracy
  • Timeline: Week 3
  • Dependencies: Q4.1

Q4.6: Content Quality Metrics

  • Question: What metrics best measure the quality of Diataxis-organized documentation?
  • Priority: LOW
  • Research Method: Quality metric research, correlation analysis
  • Success Criteria: Validated quality metrics that predict user satisfaction
  • Timeline: Week 4+
  • Dependencies: Q4.2, Q4.5

Domain 5: GitHub Pages Deployment Research (ADR-005)​

Priority: HIGH - Implementation Critical​

Workflow Optimization Questions​

Q5.1: SSG-Specific Workflow Performance

  • Question: What are the optimal GitHub Actions configurations for each supported SSG?
  • Priority: CRITICAL
  • Research Method: Workflow benchmarking, optimization testing
  • Success Criteria: Optimized workflows reduce build times by >30%
  • Timeline: Week 1-2
  • Dependencies: Q3.2

Q5.2: Advanced Caching Strategies

  • Question: What caching strategies provide maximum build performance in GitHub Actions?
  • Priority: HIGH
  • Research Method: Caching pattern research, performance testing
  • Success Criteria: Cache strategies reduce build times by >50% for incremental changes
  • Timeline: Week 2
  • Dependencies: Q5.1

Q5.3: Build Failure Diagnosis and Recovery

  • Question: How can we implement intelligent build failure diagnosis and automatic recovery?
  • Priority: HIGH
  • Research Method: Error pattern analysis, recovery strategy development
  • Success Criteria: Automatic recovery for >70% of common build failures
  • Timeline: Week 3
  • Dependencies: Q5.1

Q5.4: Multi-Environment Deployment Strategies

  • Question: What strategies support deployment to multiple environments (staging, production)?
  • Priority: MEDIUM
  • Research Method: Deployment pattern research, environment management
  • Success Criteria: Seamless multi-environment deployment capabilities
  • Timeline: Week 4
  • Dependencies: Q5.1, Q5.2

Security and Compliance Questions​

Q5.5: Workflow Security Best Practices

  • Question: What security best practices should be enforced in generated GitHub Actions workflows?
  • Priority: HIGH
  • Research Method: Security research, vulnerability analysis
  • Success Criteria: Security-hardened workflows with minimal attack surface
  • Timeline: Week 2-3
  • Dependencies: Q5.1

Q5.6: Dependency Vulnerability Management

  • Question: How can we automatically manage and update vulnerable dependencies in workflows?
  • Priority: MEDIUM
  • Research Method: Dependency scanning research, automation development
  • Success Criteria: Automated vulnerability detection and resolution
  • Timeline: Week 3
  • Dependencies: Q5.5

Q5.7: Secrets and Environment Management

  • Question: What are the best practices for managing secrets and environment variables in automated deployments?
  • Priority: MEDIUM
  • Research Method: Security pattern research, credential management
  • Success Criteria: Secure secrets management without user complexity
  • Timeline: Week 3
  • Dependencies: Q5.5

Monitoring and Troubleshooting Questions​

Q5.8: Deployment Health Monitoring

  • Question: How can we implement comprehensive health monitoring for deployed documentation sites?
  • Priority: MEDIUM
  • Research Method: Monitoring tool research, health check development
  • Success Criteria: Comprehensive health monitoring with actionable alerts
  • Timeline: Week 4
  • Dependencies: Q5.1

Q5.9: Performance Optimization Recommendations

  • Question: How can we provide automated performance optimization recommendations for deployed sites?
  • Priority: LOW
  • Research Method: Performance analysis research, optimization pattern development
  • Success Criteria: Automated performance recommendations that improve site speed
  • Timeline: Week 4+
  • Dependencies: Q5.8

Domain 6: MCP Tools API Research (ADR-006)​

Priority: HIGH - User Interface Critical​

API Design and Usability Questions​

Q6.1: Tool Parameter Schema Optimization

  • Question: What parameter schema designs provide the best balance of flexibility and usability?
  • Priority: HIGH
  • Research Method: API design research, usability testing
  • Success Criteria: Parameter schemas that are intuitive and comprehensive
  • Timeline: Week 1-2
  • Dependencies: None

Q6.2: Response Format Standardization

  • Question: What response formats provide optimal client integration and user experience?
  • Priority: HIGH
  • Research Method: Format analysis, client integration testing
  • Success Criteria: Standardized formats that simplify client development
  • Timeline: Week 2
  • Dependencies: Q6.1

Q6.3: Error Handling and User Guidance

  • Question: How can we provide the most helpful error messages and recovery guidance?
  • Priority: HIGH
  • Research Method: Error analysis, user experience research
  • Success Criteria: Error messages that enable users to resolve issues >90% of the time
  • Timeline: Week 2-3
  • Dependencies: Q6.1

Q6.4: Progressive Complexity Disclosure

  • Question: How can we design APIs that are simple for beginners but powerful for experts?
  • Priority: MEDIUM
  • Research Method: API design pattern research, user journey analysis
  • Success Criteria: APIs that scale from simple to complex use cases seamlessly
  • Timeline: Week 3
  • Dependencies: Q6.1, Q6.2

Validation and Security Questions​

Q6.5: Comprehensive Input Validation

  • Question: What validation strategies ensure robust security and user-friendly error reporting?
  • Priority: HIGH
  • Research Method: Validation framework research, security testing
  • Success Criteria: Validation that prevents all security issues while providing clear feedback
  • Timeline: Week 2
  • Dependencies: Q6.1

Q6.6: Performance and Caching Optimization

  • Question: How can we optimize API performance through intelligent caching and response optimization?
  • Priority: MEDIUM
  • Research Method: Performance testing, caching strategy research
  • Success Criteria: API response times <1 second for all operations
  • Timeline: Week 3
  • Dependencies: Q6.2

Integration and Extension Questions​

Q6.7: Client Integration Patterns

  • Question: What integration patterns work best for different types of MCP clients?
  • Priority: MEDIUM
  • Research Method: Integration testing, client developer feedback
  • Success Criteria: Integration patterns that simplify client development
  • Timeline: Week 3-4
  • Dependencies: Q6.2, Q6.4

Q6.8: API Extension and Versioning

  • Question: How can we design APIs that support future extensions without breaking existing clients?
  • Priority: LOW
  • Research Method: Versioning strategy research, extension pattern analysis
  • Success Criteria: Extension mechanisms that maintain backward compatibility
  • Timeline: Week 4
  • Dependencies: Q6.1, Q6.2

Cross-Domain Integration Research​

Priority: MEDIUM - System Integration​

End-to-End Workflow Questions​

Q7.1: Complete Workflow Orchestration

  • Question: How can we optimize the complete workflow from repository analysis to deployed documentation?
  • Priority: HIGH
  • Research Method: Workflow analysis, performance optimization
  • Success Criteria: End-to-end workflow completion in <10 minutes for typical projects
  • Timeline: Week 3-4
  • Dependencies: All previous domains

Q7.2: Error Recovery Across Tools

  • Question: How can we implement robust error recovery that spans multiple tool invocations?
  • Priority: MEDIUM
  • Research Method: Error pattern analysis, recovery strategy development
  • Success Criteria: Graceful recovery from failures at any workflow stage
  • Timeline: Week 4
  • Dependencies: Q7.1

Q7.3: Performance Monitoring and Optimization

  • Question: How can we monitor and optimize performance across the entire system?
  • Priority: MEDIUM
  • Research Method: Performance monitoring research, optimization strategies
  • Success Criteria: System-wide performance monitoring and optimization recommendations
  • Timeline: Week 4
  • Dependencies: Q7.1

Quality Assurance and Validation​

Q7.4: Integration Testing Strategies

  • Question: What testing strategies ensure reliable operation across all components?
  • Priority: MEDIUM
  • Research Method: Testing framework research, integration test development
  • Success Criteria: Comprehensive integration tests with >95% coverage
  • Timeline: Week 4
  • Dependencies: All previous domains

Q7.5: User Acceptance Validation

  • Question: How can we validate that the complete system meets user needs and expectations?
  • Priority: LOW
  • Research Method: User research, acceptance testing
  • Success Criteria: User satisfaction scores >85% in testing
  • Timeline: Week 4+
  • Dependencies: Q7.1, Q7.4

Research Execution Framework​

Research Methodology​

  1. Literature Review: Systematic review of existing solutions and best practices
  2. Prototype Development: Small-scale implementations to validate approaches
  3. Performance Testing: Quantitative analysis of performance characteristics
  4. Expert Consultation: Validation with domain experts and practitioners
  5. Community Research: Analysis of community practices and feedback

Success Criteria Framework​

Each research question includes:

  • Quantitative Metrics: Measurable success criteria
  • Qualitative Assessments: Expert validation and user feedback
  • Risk Mitigation: Identification of potential issues and solutions
  • Implementation Guidance: Actionable recommendations for development

Documentation Requirements​

All research outcomes must be documented with:

  • Executive Summary: Key findings and recommendations
  • Detailed Analysis: Comprehensive research methodology and results
  • Implementation Recommendations: Specific guidance for development
  • Risk Assessment: Identified risks and mitigation strategies
  • Follow-up Actions: Additional research or validation needed

Timeline and Prioritization​

Week 1 Focus: Critical path items (Q1.1, Q2.1, Q3.1, Q5.1) Week 2 Focus: High priority foundational research Week 3 Focus: Integration and optimization research Week 4 Focus: Advanced features and system integration

Quality Assurance​

  • Peer Review: All research findings reviewed by team members
  • Expert Validation: Critical decisions validated by external experts
  • Prototype Validation: Key approaches validated through working prototypes
  • Documentation Standards: All research properly documented and archived

Research Output Organization​

File Structure​

docs/research/
├── research-questions-2025-01-14.md          (this file)
├── domain-1-mcp-architecture/
├── domain-2-repository-analysis/
├── domain-3-ssg-recommendation/
├── domain-4-diataxis-integration/
├── domain-5-github-deployment/
├── domain-6-api-design/
├── cross-domain-integration/
└── research-findings-summary.md

Progress Tracking​

Research progress will be tracked using:

  • Weekly Status Reports: Progress on each research domain
  • Risk Register: Ongoing tracking of identified risks and mitigations
  • Decision Log: Record of key decisions made based on research findings
  • Implementation Readiness Assessment: Regular evaluation of readiness to begin development

Total Research Questions: 47 questions across 6 domains
Critical Path Questions: 6 questions requiring immediate attention
High Priority Questions: 19 questions for weeks 1-2
Estimated Research Duration: 4 weeks
Success Metrics: Quantitative criteria for each research area

This comprehensive research framework ensures systematic validation of all ADR decisions and provides the foundation for confident implementation of the DocuMCP project.