Enables persistent, full-text-searchable context for AI agents, including session tracking, event logging, todo management, and tagged context retrieval.
Provides persistent session memory for AI assistants, enabling them to store, search, and retrieve conversation summaries across sessions via the Model Context Protocol.
A session-scoped memory layer for LLMs that enables AI assistants to explicitly store and retrieve notes, decisions, and context within a single conversation, ensuring focus without cross-session data contamination.
Enables MCP-compatible AI clients to store and recall voice conversation context by caching user and AI utterances, supporting formatted context summaries for multi-turn voice interactions.
Enables AI-augmented software delivery through an append-only process record, with hooks for capturing decisions, session outcomes, and commit boundaries, and provides session priming with recency-based context.