mcphub / docs /features /monitoring.mdx
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---
title: 'Monitoring & Logging'
description: 'Monitor your MCP servers and analyze system logs with MCPHub'
---
## Overview
MCPHub provides comprehensive monitoring and logging capabilities to help you track server performance, debug issues, and maintain system health.
## Real-time Monitoring
### 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)
### Health Check Configuration
Configure health checks for your MCP servers:
```json
{
"healthCheck": {
"enabled": true,
"interval": 30000,
"timeout": 5000,
"retries": 3,
"endpoints": {
"ping": "/health",
"tools": "/tools/list"
}
}
}
```
### Monitoring API
Get monitoring data programmatically:
```bash
# 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
```
## Logging System
### 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
### Log Configuration
Configure logging in your environment:
```bash
# 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
```
### Structured Logging
MCPHub uses structured logging for better analysis:
```json
{
"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"
}
```
## Log Management
### Log Storage Options
#### File-based Logging
```yaml
# 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
```
#### Database Logging
```json
{
"logging": {
"database": {
"enabled": true,
"table": "logs",
"retention": "30d",
"indexes": ["timestamp", "level", "server"]
}
}
}
```
#### External Log Services
```bash
# 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
```
### Log Rotation
Automatic log rotation configuration:
```json
{
"logRotation": {
"enabled": true,
"maxSize": "100MB",
"maxFiles": 10,
"compress": true,
"interval": "daily"
}
}
```
## Metrics Collection
### System Metrics
MCPHub collects various system metrics:
```javascript
// 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"
}
}
}
```
### Custom Metrics
Add custom metrics for your use case:
```javascript
// 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),
});
```
## Alerting
### Alert Configuration
Set up alerts for critical conditions:
```json
{
"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"]
}
}
}
```
### Notification Channels
#### Email Notifications
```bash
# 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
```
#### Slack Integration
```bash
# Slack webhook
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/...
SLACK_CHANNEL=#mcphub-alerts
```
#### Webhook Notifications
```json
{
"webhooks": [
{
"url": "https://your-service.com/webhooks/mcphub",
"events": ["server.down", "error.rate.high"],
"headers": {
"Authorization": "Bearer your-token"
}
}
]
}
```
## Log Analysis
### Query Logs
Use the logs API to query and analyze logs:
```bash
# 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"
```
### Log Aggregation
Aggregate logs for insights:
```bash
# 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"
```
## Performance Monitoring
### Response Time Tracking
Monitor MCP server response times:
```javascript
// Response time metrics
{
"server": "github-mcp",
"tool": "search_repositories",
"metrics": {
"calls": 156,
"avgTime": 234,
"minTime": 89,
"maxTime": 1205,
"p50": 201,
"p95": 567,
"p99": 892
}
}
```
### Error Rate Monitoring
Track error rates and patterns:
```bash
# 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"
```
## Integration with External Tools
### Prometheus Integration
Export metrics to Prometheus:
```yaml
# prometheus.yml
scrape_configs:
- job_name: 'mcphub'
static_configs:
- targets: ['localhost:3000']
metrics_path: '/api/monitoring/prometheus'
scrape_interval: 30s
```
### Grafana Dashboards
Import MCPHub Grafana dashboard:
```json
{
"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"
}
]
}
]
}
}
```
### ELK Stack Integration
Configure Logstash for log processing:
```ruby
# 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}"
}
}
```
## Troubleshooting
### Common Monitoring Issues
**Missing Metrics**
```bash
# Check metrics endpoint
curl http://localhost:3000/api/monitoring/health
# Verify configuration
grep -r "monitoring" /path/to/config/
```
**Log File Issues**
```bash
# 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**
```bash
# 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
```
### Debug Mode
Enable debug logging for troubleshooting:
```bash
# Enable debug mode
DEBUG=mcphub:* npm start
# Or set environment variable
export DEBUG=mcphub:monitoring,mcphub:logging
```
## Best Practices
### 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
### Monitoring Setup
- Configure appropriate health check intervals
- Set up alerts for critical conditions
- Monitor both system and application metrics
- Use dashboards for visual monitoring
### 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
### Security Considerations
- Sanitize sensitive data in logs
- Secure access to monitoring endpoints
- Use authentication for external integrations
- Encrypt log transmission when using external services