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

Slipstream - Built by Vektor Memory - a persistent multi-layered memory architecture. 4-layer associative graph memory (MAGMA) with autonomous REM cycle, CLI, DXT-MCP Cloak Tools.

A knowledge-graph-based memory system for AI agents that enables persistent information storage between conversations.

Memory for AI agents that can't hallucinate — answers only from stored facts with a citation, or honestly abstains. Provable forgetting (GDPR), valid-time, Merkle proofs, deterministic. MCP server, CPU-only, zero dependencies.

Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.

Local-first, governable long-term memory for AI agents. Provides SQLite-backed storage, cross-session recall, and traceable memory corrections through a standard MCP interface.

A local, persistent memory system for AI coding assistants that stores decisions, patterns, and session context via MCP tools. It enables cross-session memory management using SQLite and optional vector search without external dependencies or cloud storage.

Provides persistent memory storage for AI agents with full-text search, tagging, and importance levels, enabling agents to store and retrieve memories efficiently.

Provides persistent cognitive memory for AI agents and robots with no LLM in the loop, using algorithms for storage, recall, and forgetting; supports MCP, HTTP, and ROS2.

Enables multiple AI agents to share a persistent, attributable memory space through MCP, supporting durable storage, keyword search, and event history for cross-agent continuity.

Persistent memory infrastructure for AI agents, enabling cross-session recall and autonomous memory evolution via an MCP server.

A Rust-based MCP server that provides long-term memory capabilities for AI agents using keyword-based storage and retrieval. It supports isolated namespaces for different users or projects, allowing LLMs to remember and recall information across sessions.

MCP server providing shared working memory for collaborative AI agents, with real-time notes and LLM-consolidated structured memory bank.

Hosted memory for AI agents that learns from outcomes, with shared rooms. One key across Claude, Cursor & ChatGPT.

Hand a project over — to your next session, to Cursor/Codex/Gemini, to your successor — with the reasons attached. Local-first memory MCP for coding agents: decisions re-injected before the agent acts, drift detection across every project you run. One SQLite file, nothing leaves your machine.

Smart memory for AI agents. Solves the Karpathy problem: memories decay, topics are frequency-weighted, one-time questions don't become obsessions. 7 tools. Zero deps.

Persistent, structured memory server for AI agents using the Model Context Protocol, with categorized storage and tools to add, get, delete, and list memories.

Manages an agent's long-term memories as versioned markdown files with searchable SQLite indexes, supporting lifecycle states, conflict-gated recall, revision, and explicit forgetting without automatic deletion.

A zero-dependency, file-based persistent memory system for AI agents with tiered memory, Ebbinghaus decay, and keyword retrieval.

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

Enables AI agents to persist memories across sessions and recall them through graph-traversal spreading activation over interconnected neurons with explicit relationship types, supporting multi-hop reasoning fully offline without embedding API costs.