"Understanding Memory or Memory-Related Topics" matching MCP servers:

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.

MCP server that connects Claude Code to Substrate organizational memory, providing tools for searching, reading, querying, and writing memory, with automatic capture of conversation turns.

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

MCP server providing persistent memory for AI applications, enabling Claude to store and recall memories with hybrid search and knowledge graph.

Exposes tools that let an agent search a local Markdown-based memory store, fetch full cards by id, write new knowledge cards that are indexed immediately, and inspect or rebuild the SQLite index. All retrieval runs locally over Chinese-friendly full-text search with graded exact/prefix matching, so agents without a memory system can recall prior notes while existing Markdown files stay read-only.

Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

Enables agents to manage persistent long-term memory through MCP tools for searching, adding, updating, giving feedback, and forgetting memories, with automated pipelines for redaction, distillation, and reconciliation.

An MCP server providing long-term memory for LLMs via hybrid search (FTS5 + vector) stored in SQLite, with time-decay scoring and support for multiple AI assistants.

Local-first persistent memory layer for MCP agents with hybrid search, file ingestion, and GDPR compliance.

MCP server for persistent, semantic memory across AI sessions; store context, decisions, and learnings and recall them with natural language search.

Enables persistent memory management with semantic vector recall, BM25 keyword search, and 3-way fused retrieval combining lexical, semantic, and tag-based signals.

Provides persistent memory with semantic search for MCP-based AI agents, enabling them to store and recall information across sessions using vector embeddings.

Cognitive memory engine for AI agents with 5,100+ knowledge modules, circadian rhythm awareness, emotional state tracking (PAD model), and hybrid semantic search. Supports persistent per-user memory, project-scoped contexts, and multi-protocol access.

Nexus Memory gives every MCP-compatible agent one persistent, self-hosted shared memory with hybrid retrieval, drift detection, and anti-poisoning features.

Persistent project memory for coding agents, kept in a local SQLite store with FTS5 search: search and list memories by topic, read one with its history, add a fact, show the store's statistics, and read or regenerate the PROGRESS.md handoff. Pure standard-library Python; no network.

A persistent memory MCP server for Claude Code that automatically saves conversations and retrieves relevant history across sessions to provide context.

Provides AI coding agents with a hybrid cognitive memory engine that reduces token usage, prevents amnesia, detects repetitive error loops, and retrieves relevant code context through MCP.

A lightweight, local RAG memory store for MCP agents that enables recording, retrieval, updating, and visualization of persistent memories across runs.