Enables AI agents to query live schema, lineage, and query-context across data warehouses, dbt projects, orchestration systems, and BI tools via MCP tools.
Turns warehouse/lakehouse tables into a governed entity-relationship knowledge graph exposed through MCP, enabling AI agents to answer multi-table business questions without hard-coded SQL or large schema prompts.
Enables AI agents to securely query PostgreSQL with pgvector, DynamoDB, and MongoDB Atlas with Vector Search through a read-only, allowlisted MCP interface.
Serves an automatically inferred semantic layer from your warehouse over MCP, enabling AI agents to query with correct business context, joins, and filters.