Enables AI coding agents to access persistent, structured product context (personas, journeys, specs, decisions, domain rules) on demand, eliminating the need to re-explain product knowledge each session.
Routes coding agents to the most relevant project documentation (decisions, intent, constraints) with provenance and freshness, providing tools for task routing, knowledge search, and document context.
Enables AI coding agents to retrieve developer context, semantic memory, decisions, and checkpoints across sessions through hybrid full-text and vector search, with token-budgeted retrieval for task-relevant context.
A passive context server that stores product knowledge, generates structured prompts, and coordinates multi-agent workflows via the Model Context Protocol, enabling AI coding tools to share a full picture of the product.
Provides AI coding agents with persistent memory by recording sessions and normalizing them into a searchable knowledge graph, then delivering relevant context at the start of the next session.
