A governed MCP server that enforces a trust layer between AI agents and databases, requiring sign-off on joins and metrics and producing auditable receipts for every query.
A vendor-neutral, release-aware context contract and MCP runtime that provides reliable data agents with compact metadata, semantic definitions, and validated SQL compilation.
A read-only MCP server that enables users to query Databricks SQL, browse metadata, and monitor Delta Lake tables. It also supports tracking Databricks Jobs, DLT Pipelines, and cluster metrics through natural language interfaces.
A secure, declarative MCP runtime that turns YAML configs into MCP servers with trust enforcement, credential brokering, and tamper-evident audit logging.
An MCP server that integrates with DataHub to track and score the reliability of AI agent actions. It provides a trust gateway that stamps every piece of context with its author's settled trust score.
A governed analytics MCP server that provides LLM agents with safe, read-only access to data warehouses through a layered safety pipeline including AST validation, column/row governance, PII masking, cost limits, and audit.