Enables enterprise AI agents to query governed data lineage, PII-aware schema documentation, and semantic metadata from SQL logs via MCP, with role-based access and vector search.
Serves an automatically inferred semantic layer from your warehouse over MCP, enabling AI agents to query with correct business context, joins, and filters.
Data observability for AI agents. Query alerts, monitor freshness, investigate schema drift, and trace lineage across your data warehouse via 53 MCP tools.
MCP server providing read-only Snowflake metadata tools (schemas, tables, queries, lineage) for agentic data pipeline generation, enabling natural-language-to-pipeline workflows with dbt, Airflow, and Great Expectations.
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.