Detect metric anomalies and alert teams in context
AirOps MCP continuously monitors your key business metrics across connected data sources. When it detects an anomaly — an unexpected spike, a sudden drop, or a deviation from the established baseline — it doesn’t just fire a raw alert. It aggregates context: recent deploys from GitHub, campaign changes from your ad platform, and correlated metrics from adjacent systems. The alert that hits Slack explains what happened, why it probably happened, and what to check first.
Process
Define your monitored metrics
Select the KPIs to watch — conversion rate, MRR, ad spend efficiency, or any custom metric from your data warehouse.
Set your baseline and thresholds
Configure the rolling window for baseline calculation and the deviation percentage that triggers an alert. AirOps can also auto-learn baselines.
Connect your context sources
Link GitHub, your ad platforms, and your product analytics tool. When an anomaly fires, AirOps pulls recent changes from these sources to explain it.
Configure alert delivery
Set the Slack channel, email list, or PagerDuty policy that receives the alert. Include the right stakeholders for each metric.
Review and tune
After the first week, review alert frequency and false-positive rate. Adjust thresholds and context sources to reduce noise.
Key benefits
Publish 10,000+ pages from a single workflow run
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