"Understanding Memory and Related Concepts" matching MCP servers:

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

An MCP server that stores project memory in Supabase, allowing AI tools to persist context, notes, and decisions across sessions. Enables Claude Code, Codex, and similar assistants to maintain long-term project continuity through persistent memory storage.

Local-first, auditable memory for AI agents. Provides durable context for MCP hosts with SQLite storage, CLI, and MCP tools for memory management.

Persistent knowledge graph MCP server with SQLite backend, offering graph traversal, fuzzy search, and temporal queries for entities and relations. It serves as a drop-in replacement for the npm mcp-server-memory with enhanced capabilities.

Enables coding agents to query and modify a SQLite database through twelve SQL-based tools, with safety enforced server-side via statement policies, protected tables, result caps, and snapshots. It also provides an append-only, hash-chained memory log with checkpoints so agents can record events and resume context across sessions.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

A lightweight, fully local MCP server that provides AI coding tools with a shared SQLite memory store and built-in conflict arbitration, enabling structured memory sharing across tools like ZCode, Codex, Cursor, and Claude Code without external dependencies.

A knowledge graph memory server using SQLite to provide persistent, isolated contexts for organizing information into searchable categories like work and personal projects. It features unique ID-based operations and a token-efficient serialization format designed to optimize interactions with LLMs.

A Model Context Protocol server that allows users to store, retrieve, update, and delete memories using SQLite storage.

A drop-in replacement for Anthropic's memory server that utilizes SQLite to ensure data integrity and concurrent access. It enhances the original functionality with semantic search capabilities using vector embeddings and ONNX models.

Enables storing and querying memories in a Neo4j knowledge graph with automatic entity extraction. Supports adding episodes, searching entities and relationships, and managing graph data through natural language.

An MCP server that gives AI agents a private, durable memory of people, providing a personal people graph in PostgreSQL with tools to search, remember, and connect people, plus imports from LinkedIn, Google Contacts, and WhatsApp, and a browser UI.

An MCP server for neuroanatomically-inspired memory consolidation using Neo4j and semantic search, enabling episodic memory encoding, semantic retrieval, and graph operations.

Provides persistent memory and knowledge graph capabilities for AI assistants using local SQLite storage. Enables creating, searching, and managing entities, relationships, and observations with vector search support across conversations.

A self-hosted MCP server that provides AI assistants with a shared, persistent SQLite-backed memory for storing and retrieving project context, decisions, and discoveries. It enables cross-session continuity and team-wide knowledge sharing to keep AI coding tools aligned and informed.

MCP server for MongoDB-powered memory bank management with multi-project isolation, version control, and real-time statistics.

Persistent memory server for CMS Combine lessons, enabling saving and searching confirmed error-cause-fix chains across sessions and users.

Provides knowledge graph functionality for managing entities, relations, and observations in memory with strict validation rules to maintain data consistency.

Implements long-term memory capabilities for AI assistants using PostgreSQL with pgvector for efficient vector similarity search, enabling semantic retrieval of stored information.