Enables AI agents to query live schema, lineage, and query-context across data warehouses, dbt projects, orchestration systems, and BI tools via MCP tools.
Zero-config data quality monitoring as MCP tools. Profiles a warehouse (Postgres, BigQuery, Snowflake, MySQL, DuckDB), detects anomalies, and gates CI — read-only with the connection resolved server-side, never via the model.
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.
AI-driven MCP server that audits, profiles, detects schema drift, and auto-generates documentation for dbt projects, enabling natural language interaction with your dbt project's health.
Open-source agentic schema layer. Define metrics once in YAML, query governed data from any warehouse (Snowflake, BigQuery, Databricks, PostgreSQL, DuckDB) via MCP.
Open-source autonomous agent swarm of 15 MCP-native AI agents for data engineering — catalog, quality, incidents, schema evolution, governance, migration, observability, ML. 212+ tools, Apache 2.0. Works with Claude Code, Cursor, ChatGPT, and any MCP client.