Getting Started with DocuMCP
This tutorial will guide you through setting up and using DocuMCP's intelligent documentation deployment system with memory-enhanced capabilities.
Prerequisites
Before you begin, ensure you have:
- Node.js 16+ installed
- Access to a GitHub repository
- Claude Code or another MCP-compatible client
- Basic familiarity with documentation workflows
Step 1: Initial Repository Analysis
Start by analyzing your repository to understand its characteristics and documentation needs:
{
"path": "/path/to/your/project",
"depth": "standard"
}
This will analyze your project and return:
- Project structure: File counts, languages used, and organization
- Dependencies: Production and development packages detected
- Documentation status: Existing docs, README, contributing guidelines
- Smart recommendations: Primary language, project type, team size estimates
- Unique analysis ID: For use in subsequent steps
Example response snippet:
{
"id": "analysis_abc123xyz",
"structure": {
"totalFiles": 150,
"languages": { ".ts": 45, ".js": 12, ".md": 8 },
"hasTests": true,
"hasCI": true
},
"dependencies": {
"ecosystem": "javascript",
"packages": ["react", "typescript"]
},
"recommendations": {
"primaryLanguage": "typescript",
"projectType": "library"
}
}
Step 2: Memory-Enhanced SSG Recommendation
Next, get intelligent recommendations powered by DocuMCP's memory system:
{
"analysisId": "analysis_abc123xyz",
"preferences": {
"ecosystem": "javascript",
"priority": "features"
}
}
The memory system leverages patterns from 130+ previous projects to provide:
- Confidence-scored recommendations (e.g., Docusaurus with 85% confidence)
- Historical success data (69% deployment success rate insights)
- Pattern-based insights (Hugo most common with 98 projects, but Docusaurus optimal for TypeScript)
- Similar project examples to learn from successful configurations
Example recommendation response:
{
"recommended": "docusaurus",
"confidence": 0.85,
"reasoning": [
"JavaScript/TypeScript ecosystem detected",
"Modern React-based framework aligns with project stack",
"Strong community support and active development"
],
"alternatives": [
{
"name": "MkDocs",
"score": 0.75,
"pros": ["Simple setup", "Great themes"],
"cons": ["Limited React component support"]
}
]
}
Step 3: Configuration Generation
Generate optimized configuration files for your chosen SSG:
// Generate Docusaurus configuration
{
"ssg": "docusaurus",
"projectName": "Your Project",
"projectDescription": "Your project description",
"outputPath": "/path/to/your/repository"
}
Step 4: Diataxis Structure Setup
Create a professional documentation structure following the Diataxis framework:
// Setup documentation structure
{
"path": "/path/to/your/repository/docs",
"ssg": "docusaurus",
"includeExamples": true
}
This creates four optimized sections:
- Tutorials: Learning-oriented guides
- How-to Guides: Problem-solving instructions
- Reference: Information-oriented technical docs
- Explanation: Understanding-oriented background
Step 5: GitHub Pages Deployment
Set up automated deployment with security best practices:
// Deploy to GitHub Pages
{
"repository": "/path/to/your/repository",
"ssg": "docusaurus",
"branch": "gh-pages"
}
This generates:
- GitHub Actions workflow with OIDC authentication
- Minimal security permissions (pages:write, id-token:write only)
- Automated build and deployment pipeline
Step 6: Memory System Exploration
Explore DocuMCP's advanced memory capabilities:
// Get learning statistics
{
"includeDetails": true
}
// Recall similar projects
{
"query": "typescript documentation",
"type": "recommendation",
"limit": 5
}
The memory system provides:
- Pattern Recognition: Most successful SSG choices for your project type
- Historical Insights: Success rates and common issues
- Smart Recommendations: Enhanced suggestions based on similar projects
Verification
Verify your setup with these checks:
- Documentation Structure: Confirm all Diataxis directories are created
- Configuration Files: Check generated config files are valid
- GitHub Actions: Verify workflow file in
.github/workflows/
- Memory Insights: Review recommendations and confidence scores
Summary
In this tutorial, you learned how to:
- Analyze repositories with comprehensive project profiling
- Get intelligent SSG recommendations using memory-enhanced insights
- Generate optimized configurations for your chosen static site generator
- Create Diataxis-compliant structures for professional documentation
- Set up automated GitHub Pages deployment with security best practices
- Leverage the memory system for enhanced recommendations and insights
Next Steps
- Explore Memory-Enhanced Workflows
- Read How-To Guides for specific tasks
- Check the API Reference for complete tool documentation
- Learn about Diataxis Framework principles