aegis-dq
aegis-dq/aegis-dq
Data quality checks on DuckDB, BigQuery, Athena, Databricks and Postgres, with LLM root-cause analysis of failures and proposed SQL remediations.
- Local integrations
Installation, supported tools and required credentials are maintained by the project.
Project details
- GitHub stars
- 4
- Language
- Python
- Forks
- 2
- Latest release
- v0.7.05mo ago
- Activity
- updated 4mo ago
- Platforms listed
- macOS, Windows, Linux
- agentic-ai
- airflow
- data-engineering
- data-quality
- dbt
- duckdb
- langgraph
- llm
First MCP server?Start with the basics
dbt integration: dbt Core and Cloud CLI, project metadata discovery, model information and semantic layer queries.
Operational ontology reference implementation: tools generated from a typed business domain model, with rule-checked, audited writes to systems of record.
Interact with the Keboola Connection data platform: list and access data from the Keboola Storage API.
Apache Superset: dashboards, charts, datasets, SQL Lab, security (users, roles, RLS, groups) and permissions audit, with built-in safety validations.
Run SQL queries, list jobs and get job status via the Databricks API.
Kafka Schema Registry management across multiple registries, including schema migration.
Brazilian agricultural data: prices, crop estimates, climate and deforestation from public sources including CEPEA, CONAB, IBGE, INPE and B3.
Swiss open data: transport, weather, geodata, companies, parliament and more.