TinyContext provides a local, token-efficient memory layer for AI agents. It enables saving and recalling memories via MCP tools, using hybrid BM25 and dense retrieval to return only context that fits the requested token budget.
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 unified context layer for Cursor's agent with lossless token savings and verifiable memory, enabling efficient code exploration and cross-session continuity.
Provides persistent, local-first long-term memory for LLMs using Voronoi-partitioned vector storage and local embeddings. It enables users to store, recall, and automatically retrieve project context and preferences entirely on their own machine.
