Enables AI agents to explore Unity Catalog metadata, execute SQL queries, and analyze data lineage including notebooks and jobs, empowering autonomous data discovery and query generation in Databricks.
Enables AI agents to access enterprise data from Unity Catalog (vector search, functions, Genie spaces) and perform developer actions in Databricks like managing notebooks and running jobs.
Exposes schema, lineage, and data-quality trust signals from a SQLite-backed catalog as MCP tools, enabling AI agents to answer grounded questions about datasets without hallucinating.
Gives LLM agents access to local and remote data via databases, files, graphs, and structured documents, along with a full data science toolkit for analysis and modeling.
Exposes Iceberg-backed ontology objects, links, and actions as typed MCP tools for LLM agents, enabling governed data access and operations without raw SQL.