An MCP server that enables AI assistants to create and manage persistent SQLite databases through natural language without requiring SQL knowledge. It allows users to propose schemas, store records, and perform complex queries across multiple databases for structured data tracking.
An MCP server that provides persistent long-term memory for AI agents via local SQLite storage with low token overhead, enabling memory storage, retrieval, and management across sessions.
A local, fully-offline MCP memory server that enables persistent storage and retrieval of information using SQLite with both keyword and semantic vector search capabilities.
MCP server providing persistent memory management for AI agents using SQLite and FTS5, enabling storage, full-text search, and recall of memories with namespace isolation.
A database-backed MCP server that acts as a project memory bank, enabling AI assistants to store, retrieve, and search structured context like decisions, tasks, and architecture using SQLite and vector embeddings.
An MCP server that provides persistent memory for AI agents by storing session snapshots, factual memories, and conversation summaries. It enables seamless continuity between interactions by allowing agents to restore previous emotional states and recall relevant past experiences.
