Multi-dimensional data quality validation and statistical anomaly detection for LLM training data, with auto-fix pipeline and MCP tools for AI IDE integration.
Agentic data quality MCP server — runs structured validation rules against warehouses (DuckDB, BigQuery, Athena, Databricks, Postgres), diagnoses failures with LLM root cause analysis, and proposes SQL remediations. Full audit trail of every AI decision.
Provides AI agents with data validation, transformation, and normalization capabilities, including JSON schema validation, CSV processing, data normalization, text cleaning, and dataset merging.
Provides AI agents with safe, governed read access to industrial control systems (OPC-UA, Modbus, S7, Mitsubishi, MTConnect, MQTT/Sparkplug) plus cross-protocol diagnostics for troubleshooting data breaks, alarm floods, and unhealthy tags.