Transforms static coding standards into a queryable live data store for AI agents, delivering task-specific rules and fix guidance on demand. This optimizes context window usage through progressive disclosure, ensuring agents apply relevant governance without loading massive documentation.
Securely connects AI agents to multiple databases simultaneously while enabling collaborative learning from team query patterns, all while keeping data private by running locally.
Enables AI agents to understand and query your database safely by providing a semantic layer of metadata, with tools to search, explain, validate, and generate safe SQL.
A compact backend platform exposing a scoped MCP server for agents, with SQLite data plane, embedded Studio, auth, storage, and realtime. Default read-only agent access with opt-in read-write mutations via isolated preview branches and exact-SQL approval before production promotion.