"Understanding how memory is stored or memory storage methods" matching MCP servers:

A shared memory and coordination server for multiple AI coding agents, built on the Model Context Protocol (MCP).

Enables AI agents to persist and share durable memory — appending session logs with checkpoints and handoffs, claiming and completing tasks, and recording decision records — all stored as plain Markdown and JSONL files in a git repository. Everything written is full-text searchable, and the server speaks MCP so MCP-aware clients can plug in directly with zero vendor lock-in.

An advanced contextual memory server for agent orchestration providing chronological history, semantic vector search via Redis Stack, and temporary scratchpad storage. It also enables context compression through history rollups and facilitates inter-agent communication using a Redis-based Pub/Sub system.

Model Context Protocol (MCP) memory server built with Azure Functions and TypeScript, providing persistent knowledge graph storage for your preferred MCP client. Inspired by and forked from @modelcontextprotocol/server-memory

Provides MCP tools for persistent, cross-session memory via Cloudflare Agent Memory, enabling agents to store, recall, ingest, summarize, and manage memory namespaces.

Provides a centralized MCP-based system for managing and accessing multi-project memory banks remotely, with features like project isolation, file structure validation, and type-safe operations.

Provides a shared memory bridge for AI agents (QClaw, Claude Code, Codex) allowing them to store, search, and retrieve notes, decisions, and conclusions via MCP tools, using local SQLite with optional TencentDB integration.

An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.

A production-ready MCP server that enables multiple AI agents to collaborate through a shared, concurrency-safe memory space. It supports advanced search, full CRUD operations, and automatic backups to facilitate asynchronous communication between agents.

An enhanced MCP server that provides intelligent memory and task management for AI assistants, featuring semantic search, automatic task extraction, and knowledge graphs to help manage development workflows.

Enables AI agents to share persistent memory via an MCP server using SQLite, supporting multi-tenant, categorized knowledge with TTL and semantic links, without requiring vector databases.

A lightweight MCP server that records and reuses prompt gaps — essential context missing from initial instructions — so your AI assistant learns from every session using a plain JSONL file tracked by Git.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Provides a shared context layer for AI agent teams to improve token efficiency through context deduplication and incremental state sharing. It enables multiple agents to coordinate tasks, share real-time discoveries, and manage dependencies while significantly reducing redundant data transmission.

Eve is an agentic memory service across agents & AI tools. All agents share one memory , preferences and rules. https://evemem.com

Enables routing context and execution across AI tools like Claude, Cursor, Windsurf, and ChatGPT with a shared memory, task board, and context bus, plus local file conversion.

A local MCP server using SQLite to unify context and memory across multiple AI agents, enabling persistent decisions and preferences without re-explanation.

Verified memory infrastructure for AI agents. Every assertion signed, timestamped, and cryptographically proven. Includes session continuity across Claude Code, Cursor, and Windsurf, plus Proof Meter billing attestation.

Provides agent-readiness audits of public websites via Cloudflare's scanner, enabling users to run scans, save reports, and enforce safety boundaries from natural language.

Cost-first memory layer for MCP-capable agents that stores memories cheaply and recalls relevant slices under a hard token budget, logging receipts for every recall.