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How to Use DocuMCP Deployment Analytics

This guide shows you how to access and use DocuMCP's built-in deployment analytics to track your documentation deployment success and patterns.

Quick Setup​

# Analyze deployment patterns:
"analyze my deployment history and provide insights"

Analytics Overview​

DocuMCP provides comprehensive deployment analytics to help you understand and optimize your documentation deployment process:

Analytics Types​

  • Deployment Success Tracking: Monitor deployment success/failure rates
  • SSG Performance Analytics: Compare static site generator effectiveness
  • Build Time Metrics: Track deployment speed and optimization opportunities
  • Project Pattern Analysis: Understand which configurations work best

Built-in Analytics Features​

  • Deployment Health Scoring: 0-100 health score for your deployment pipeline
  • SSG Comparison: Compare success rates across different static site generators
  • Trend Analysis: Track deployment patterns over time
  • Knowledge Graph Integration: Learn from deployment history for better recommendations

Using Deployment Analytics​

Method 1: Generate Full Analytics Report​

# Get comprehensive deployment analytics:
"analyze my deployments and provide a full report"

This will provide:

  1. Overall deployment success rates
  2. SSG performance comparison
  3. Build time analysis
  4. Project pattern insights
  5. Recommendations for optimization

Method 2: Specific Analytics Queries​

Get SSG Statistics​

# Analyze specific SSG performance:
"show me statistics for Docusaurus deployments"

Compare SSG Performance​

# Compare multiple SSGs:
"compare deployment success rates between Hugo and Jekyll"

Get Deployment Health Score​

# Check deployment pipeline health:
"what is my deployment health score?"
# View deployment trends over time:
"show me deployment trends for the last 30 days"

Deployment Analytics Examples​

Sample Analytics Report​

// Example deployment analytics report structure
{
  "summary": {
    "totalProjects": 15,
    "totalDeployments": 42,
    "overallSuccessRate": 0.85,
    "mostUsedSSG": "docusaurus",
    "mostSuccessfulSSG": "hugo"
  },
  "patterns": [
    {
      "ssg": "docusaurus",
      "totalDeployments": 18,
      "successfulDeployments": 16,
      "failedDeployments": 2,
      "successRate": 0.89,
      "averageBuildTime": 45000,
      "projectCount": 8
    }
  ],
  "insights": [
    {
      "type": "success",
      "title": "High Success Rate",
      "description": "Excellent! 85% of deployments succeed"
    }
  ]
}

Health Score Breakdown​

// Example health score analysis
{
  "score": 78,
  "factors": [
    {
      "name": "Overall Success Rate",
      "impact": 34,
      "status": "good"
    },
    {
      "name": "Active Projects",
      "impact": 20,
      "status": "good"
    },
    {
      "name": "Deployment Activity",
      "impact": 15,
      "status": "warning"
    },
    {
      "name": "SSG Diversity",
      "impact": 9,
      "status": "warning"
    }
  ]
}

MCP Tool Integration​

// Using the analyze_deployments MCP tool directly
import { analyzeDeployments } from "./dist/tools/analyze-deployments.js";

// Get full analytics report
const report = await analyzeDeployments({
  analysisType: "full_report",
});

// Get specific SSG statistics
const docusaurusStats = await analyzeDeployments({
  analysisType: "ssg_stats",
  ssg: "docusaurus",
});

// Compare multiple SSGs
const comparison = await analyzeDeployments({
  analysisType: "compare",
  ssgs: ["hugo", "jekyll", "docusaurus"],
});

// Get deployment health score
const health = await analyzeDeployments({
  analysisType: "health",
});

Advanced Deployment Analytics​

Deployment Pattern Analysis​

# Analyze deployment patterns by technology:
"show me deployment success patterns for TypeScript projects"

# Analyze by project size:
"compare deployment success rates for small vs large projects"

# Analyze by team size:
"show deployment patterns for different team sizes"

Knowledge Graph Insights​

# Get insights from deployment history:
"what SSG works best for React projects based on deployment history?"

# Learn from similar projects:
"recommend deployment strategy based on similar successful projects"

# Analyze failure patterns:
"what are the common causes of deployment failures?"

Trend Analysis​

# Analyze deployment trends:
"show me deployment success trends over the last 6 months"

# Compare time periods:
"compare deployment performance between Q3 and Q4"

# Identify improvement opportunities:
"what deployment metrics have improved recently?"

Troubleshooting​

Common Issues​

Problem: No deployment data available Solution: Deploy at least one project to start collecting analytics data

Problem: Analytics tool returns empty results Solution: Ensure knowledge graph storage directory exists and has proper permissions

Problem: Health score seems low Solution: Review deployment failures and optimize SSG configurations

Problem: Missing deployment history Solution: Check that deployment tracking is enabled in knowledge graph

Analytics Debugging​

# Debug deployment analytics issues:
"check my deployment analytics configuration and data availability"

Best Practices​

Deployment Analytics Guidelines​

  1. Regular Deployments: Deploy frequently to build meaningful analytics data
  2. Track Failures: Learn from deployment failures to improve success rates
  3. Monitor Trends: Review analytics weekly to identify patterns
  4. Compare SSGs: Use analytics to choose the best SSG for each project type
  5. Health Monitoring: Keep deployment health score above 70

Data Quality​

  1. Consistent Tracking: Ensure all deployments are tracked in knowledge graph
  2. Clean Data: Review and clean up failed deployment records periodically
  3. Regular Analysis: Run analytics reports monthly to identify trends
  4. Documentation: Document deployment patterns and insights
  5. Team Sharing: Share analytics insights with your development team

Deployment Analytics Tools​

Built-in DocuMCP Analytics​

  • Deployment success tracking: Monitor success/failure rates
  • SSG performance analysis: Compare static site generator effectiveness
  • Build time metrics: Track deployment speed and optimization opportunities
  • Knowledge graph insights: Learn from deployment history patterns

MCP Tools Available​

  • analyze_deployments: Generate comprehensive deployment analytics
  • deploy_pages: Track deployment attempts and outcomes
  • recommend_ssg: Get SSG recommendations based on analytics

Next Steps​