Provides persistent AI agent memory using a local vector database for long-term semantic storage and short-term session scratchpads. It enables low-latency memory operations including search, storage, and bulk management without external cloud dependencies.
Enables LLMs to interact with Zvec vector database through tools for collection management, document operations, vector search, and AI-powered embeddings.
Provides a local vector memory store for AI agents with semantic search, offline embeddings, and MCP integration, enabling tools like Claude and Cursor to store and retrieve information without cloud dependencies.
Provides infinite long-term memory for AI agents with persistent, searchable storage of project details, preferences, and snippets. Reduces token costs by retrieving only relevant memories while keeping all data stored locally.
