User-owned shared memory for AI agents, providing a persistent, curated knowledge layer with hybrid search and cross-agent coordination via Postgres + pgvector.
Provides persistent, local-first memory with knowledge graph and hybrid search for AI coding agents, reducing token usage by storing decisions, patterns, and codebase context.
Provides a persistent, vendor-neutral memory layer that allows AI tools and agents to share context and knowledge across different platforms while maintaining local data ownership. It enables users to store, recall, and manage structured memories through hybrid semantic search and automated context assembly.
Universal AI memory layer that provides cross-client, cross-repo context management with semantic search, automatic code indexing, and session management. Enables persistent developer memory across projects with typed memories, graph-based relationships, and RAG-powered retrieval.
A local-first memory layer for coding agents to persist and retrieve project decisions, architecture context, and rules across multiple development sessions. It utilizes a three-tier memory model and hybrid retrieval to provide agents with durable, searchable context and a WebUI for human review.
Self-hosted memory and governance layer for AI coding agents. 28 MCP tools with hybrid search, structured knowledge capture, behavioral nudges, and git-native storage. Zero cloud dependencies.