aegis-dq/aegis-dq

Overview

Aegis-DQ is an open-source Python framework for data quality checks designed for audit-grade agentic workflows. It provides portable industry packs that bundle validation rules and documentation for specific domains, enabling systematic quality control.

Best for

Best for
Data engineers and compliance teams needing audit-ready, domain-specific data quality checks

Use cases

• Enforcing data quality rules in data pipelines
• Automating compliance checks for regulated data assets
• Integrating domain-specific validation packs into existing workflows

How to use

Install

pip install aegis-dq

Tools exposed

• rules-file
• pg-dsn
• no-llm
• llm-model
• fail-on-failure
• anthropic-api-key
• openai-api-key
• rules-checked
• pass-rate
• report-json
• Cross-table

Tested with

Claude Desktop, Cursor, VS Code, ChatGPT

Notes

Aegis-DQ is an open-source Python framework for data quality checks designed for audit-grade agentic workflows. It provides portable industry packs that bundle validation rules and documentation for specific domains, enabling systematic quality control.

3 stars on GitHub. Last updated 2026-05-27.

Use cases

• Enforcing data quality rules in data pipelines
• Automating compliance checks for regulated data assets
• Integrating domain-specific validation packs into existing workflows

Pros

• Audit-grade focus suits regulated environments
• Portable industry packs reduce rule setup time
• Open-source with a Python API for extensibility

Cons

• Limited community adoption (3 stars) suggests early stage
• Fewer integrations than mature data quality tools
• Industry packs may be sparse without clear vendor support

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.