Enables AI agents to perform read-only data hub queries including table listing, schema details, distinct values, and row-limited SELECT/aggregation, while rejecting free SQL.
Enables AI agents and assistants to work with a Databricks workspace — SQL, clusters and warehouses, notebooks, Jobs, Lakeflow pipelines, Unity Catalog, Volumes, dashboards, Genie, model serving, Vector Search, Lakebase and Apps — under a safety-first model with read/write/destructive/security classification, confirmation steps for dangerous changes, production resource protection, and a fully read-only mode. Every call is checked against the official Databricks SDK, returns typed schemas and redacted secrets, and unsupported features report an explicit error rather than faking results.
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 safe, read-only SQL access to SQLite databases for AI agents, allowing schema exploration and SELECT queries with defense-in-depth protections.
Enables AI agents to query Trino and Apache Pinot lakehouses under enforced governance, where every SQL statement is AST-validated, table-allowlisted, priced from the engine's own plan before it runs, and blocked or admitted against scan-byte and intermediate-row budgets. It also grounds agents with schema discovery tools, returns verified results with warnings instead of misleading answers, and records every tool call on an audit trail.