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Overview

MCPHub provides comprehensive monitoring and logging capabilities to help you track server performance, debug issues, and maintain system health.

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Real-time Monitoring

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Server Status Dashboard

The MCPHub dashboard provides real-time monitoring of all registered MCP servers:
  • Server Health: Online/offline status with automatic health checks
  • Response Times: Average, min, max response times per server
  • Request Volume: Requests per second/minute/hour
  • Error Rates: Success/failure ratios and error trends
  • Resource Usage: Memory and CPU utilization (when available)

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Health Check Configuration

Configure health checks for your MCP servers: 
{
  "healthCheck": {
    "enabled": true,
    "interval": 30000,
    "timeout": 5000,
    "retries": 3,
    "endpoints": {
      "ping": "/health",
      "tools": "/tools/list"
    }
  }
}

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Monitoring API

Get monitoring data programmatically: 
# Get server health status
curl http://localhost:3000/api/monitoring/health

# Get performance metrics
curl http://localhost:3000/api/monitoring/metrics?server=my-server&range=1h

# Get system overview
curl http://localhost:3000/api/monitoring/overview

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Logging System

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Log Levels

MCPHub supports standard log levels:
  • ERROR: Critical errors requiring immediate attention
  • WARN: Warning conditions that should be monitored
  • INFO: General operational messages
  • DEBUG: Detailed debugging information
  • TRACE: Very detailed trace information

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Log Configuration

Configure logging in your environment: 
# Set log level
LOG_LEVEL=info

# Enable structured logging
LOG_FORMAT=json

# Log file location
LOG_FILE=/var/log/mcphub/app.log

# Enable request logging
ENABLE_REQUEST_LOGS=true

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Structured Logging

MCPHub uses structured logging for better analysis: 
{
  "timestamp": "2024-01-20T10:30:00Z",
  "level": "info",
  "message": "MCP server request completed",
  "server": "github-mcp",
  "tool": "search_repositories",
  "duration": 245,
  "status": "success",
  "requestId": "req_123456",
  "userId": "user_789"
}

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Log Management

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Log Storage Options

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File-based Logging

# docker-compose.yml
services:
  mcphub:
    volumes:
      - ./logs:/app/logs
    environment:
      - LOG_FILE=/app/logs/mcphub.log
      - LOG_ROTATION=daily
      - LOG_MAX_SIZE=100MB
      - LOG_MAX_FILES=7

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Database Logging

{
  "logging": {
    "database": {
      "enabled": true,
      "table": "logs",
      "retention": "30d",
      "indexes": ["timestamp", "level", "server"]
    }
  }
}

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External Log Services

# Syslog integration
SYSLOG_ENABLED=true
SYSLOG_HOST=localhost
SYSLOG_PORT=514
SYSLOG_FACILITY=local0

# ELK Stack integration
ELASTICSEARCH_URL=http://localhost:9200
ELASTICSEARCH_INDEX=mcphub-logs

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Log Rotation

Automatic log rotation configuration: 
{
  "logRotation": {
    "enabled": true,
    "maxSize": "100MB",
    "maxFiles": 10,
    "compress": true,
    "interval": "daily"
  }
}

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Metrics Collection

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System Metrics

MCPHub collects various system metrics: 
// Example metrics collected
{
  "timestamp": "2024-01-20T10:30:00Z",
  "metrics": {
    "requests": {
      "total": 1547,
      "success": 1523,
      "errors": 24,
      "rate": 12.5
    },
    "servers": {
      "online": 8,
      "offline": 2,
      "total": 10
    },
    "performance": {
      "avgResponseTime": 156,
      "p95ResponseTime": 324,
      "p99ResponseTime": 567
    },
    "system": {
      "memoryUsage": "245MB",
      "cpuUsage": "15%",
      "uptime": "72h 35m"
    }
  }
}

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Custom Metrics

Add custom metrics for your use case: 
// Custom metric example
const customMetric = {
  name: 'tool_usage',
  type: 'counter',
  tags: {
    server: 'github-mcp',
    tool: 'search_repositories',
    result: 'success',
  },
  value: 1,
};

// Send to metrics endpoint
await fetch('/api/monitoring/metrics', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify(customMetric),
});

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Alerting

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Alert Configuration

Set up alerts for critical conditions: 
{
  "alerts": {
    "serverDown": {
      "condition": "server.status == 'offline'",
      "duration": "5m",
      "severity": "critical",
      "channels": ["email", "slack"]
    },
    "highErrorRate": {
      "condition": "errors.rate > 0.1",
      "duration": "2m",
      "severity": "warning",
      "channels": ["slack"]
    },
    "slowResponse": {
      "condition": "response.p95 > 1000",
      "duration": "5m",
      "severity": "warning",
      "channels": ["email"]
    }
  }
}

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Notification Channels

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Email Notifications

# Email configuration
SMTP_HOST=smtp.gmail.com
SMTP_PORT=587
SMTP_USER=alerts@yourcompany.com
SMTP_PASS=your-app-password
ALERT_EMAIL_TO=admin@yourcompany.com

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Slack Integration

# Slack webhook
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/...
SLACK_CHANNEL=#mcphub-alerts

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Webhook Notifications

{
  "webhooks": [
    {
      "url": "https://your-service.com/webhooks/mcphub",
      "events": ["server.down", "error.rate.high"],
      "headers": {
        "Authorization": "Bearer your-token"
      }
    }
  ]
}

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Log Analysis

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Query Logs

Use the logs API to query and analyze logs: 
# Get recent errors
curl "http://localhost:3000/api/logs?level=error&since=1h"

# Search logs by server
curl "http://localhost:3000/api/logs?server=github-mcp&limit=100"

# Get logs for specific request
curl "http://localhost:3000/api/logs?requestId=req_123456"

# Filter by time range
curl "http://localhost:3000/api/logs?from=2024-01-20T00:00:00Z&to=2024-01-20T23:59:59Z"

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Log Aggregation

Aggregate logs for insights: 
# Error summary by server
curl "http://localhost:3000/api/logs/aggregate?groupBy=server&level=error&since=24h"

# Request volume over time
curl "http://localhost:3000/api/logs/aggregate?groupBy=hour&type=request&since=7d"

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Performance Monitoring

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Response Time Tracking

Monitor MCP server response times: 
// Response time metrics
{
  "server": "github-mcp",
  "tool": "search_repositories",
  "metrics": {
    "calls": 156,
    "avgTime": 234,
    "minTime": 89,
    "maxTime": 1205,
    "p50": 201,
    "p95": 567,
    "p99": 892
  }
}

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Error Rate Monitoring

Track error rates and patterns: 
# Get error rates by server
curl "http://localhost:3000/api/monitoring/errors?groupBy=server&since=1h"

# Get error details
curl "http://localhost:3000/api/monitoring/errors?server=github-mcp&details=true"

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Integration with External Tools

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Prometheus Integration

Export metrics to Prometheus: 
# prometheus.yml
scrape_configs:
  - job_name: 'mcphub'
    static_configs:
      - targets: ['localhost:3000']
    metrics_path: '/api/monitoring/prometheus'
    scrape_interval: 30s

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Grafana Dashboards

Import MCPHub Grafana dashboard: 
{
  "dashboard": {
    "title": "MCPHub Monitoring",
    "panels": [
      {
        "title": "Server Status",
        "type": "stat",
        "targets": [
          {
            "expr": "mcphub_servers_online",
            "legendFormat": "Online"
          }
        ]
      },
      {
        "title": "Request Rate",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(mcphub_requests_total[5m])",
            "legendFormat": "Requests/sec"
          }
        ]
      }
    ]
  }
}

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ELK Stack Integration

Configure Logstash for log processing: 
# logstash.conf
input {
  beats {
    port => 5044
  }
}

filter {
  if [fields][service] == "mcphub" {
    json {
      source => "message"
    }

    date {
      match => [ "timestamp", "ISO8601" ]
    }
  }
}

output {
  elasticsearch {
    hosts => ["localhost:9200"]
    index => "mcphub-logs-%{+YYYY.MM.dd}"
  }
}

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Troubleshooting

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Common Monitoring Issues

Missing Metrics 
# Check metrics endpoint
curl http://localhost:3000/api/monitoring/health

# Verify configuration
grep -r "monitoring" /path/to/config/
Log File Issues 
# Check log file permissions
ls -la /var/log/mcphub/

# Verify disk space
df -h /var/log/

# Check log rotation
logrotate -d /etc/logrotate.d/mcphub
Performance Issues 
# Monitor system resources
top -p $(pgrep -f mcphub)

# Check database connections
curl http://localhost:3000/api/monitoring/database

# Analyze slow queries
curl http://localhost:3000/api/monitoring/slow-queries

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Debug Mode

Enable debug logging for troubleshooting: 
# Enable debug mode
DEBUG=mcphub:* npm start

# Or set environment variable
export DEBUG=mcphub:monitoring,mcphub:logging

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Best Practices

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Log Management

  • Use structured logging with consistent formats
  • Implement proper log levels and filtering
  • Set up log rotation and retention policies
  • Monitor log file sizes and disk usage

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Monitoring Setup

  • Configure appropriate health check intervals
  • Set up alerts for critical conditions
  • Monitor both system and application metrics
  • Use dashboards for visual monitoring

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Performance Optimization

  • Index log database tables appropriately
  • Use log sampling for high-volume scenarios
  • Implement proper caching for metrics
  • Regular cleanup of old logs and metrics

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Security Considerations

  • Sanitize sensitive data in logs
  • Secure access to monitoring endpoints
  • Use authentication for external integrations
  • Encrypt log transmission when using external services
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