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AnomalyArmor

OfficialLive

by anomalyarmor · Python

Data observability tools for engineering teams: alerts, freshness, schema drift, lineage, quality.

ai.anomalyarmor/armor-mcp (MCP)

This MCP server provides data observability tools for engineering teams, focused on alerts, freshness, schema drift, lineage, and quality. It supports integrating AI skills to monitor and manage data reliability workflows from an MCP client.

🛠️ Key Features

  • Alerts
  • Data freshness monitoring
  • Schema drift detection
  • Data lineage
  • Data quality tracking

🚀 Use Cases

  • Detect and respond to schema drift in data systems
  • Monitor data freshness and quality over time
  • Manage alerting for observability signals
  • Review lineage to understand data dependencies

⚡ Developer Benefits

  • Enables using AnomalyArmor data observability via an MCP server
  • Intended to work with tools like Claude Code and Cursor (via MCP integration)
  • Listed with SDK availability for Python (PyPI) and JavaScript (npm)

⚠️ Limitations

  • Public documentation excerpt references AI skills and monitoring/management workflows but does not specify tool names, configuration, or supported MCP client interfaces beyond the mentioned tools.