"Understanding Memory and Related Concepts" matching MCP servers:

A minimal MCP server that exposes Gemini's web and multimodal understanding (video, audio, document, image) through five dedicated tools.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

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

An MCP server that uses Google's Gemini API to analyze videos and convert them to text descriptions that Claude Code can understand and act upon.

Multi-user, file-backed MCP memory server enabling isolated namespaces and persistent memory across sessions and AI clients.

Provides AI agents with associative long-term memory using Sparse Distributed Memory, enabling recall from vague cues and interference detection.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

MCP server for zero-config, traceable long-term memory using SQLite, enabling agents to store, search, trace, and monitor memory with tools like memory_store, memory_search, and memory_health.

Personal memory service using semantic vector retrieval and knowledge graphs to persist long-term context, supporting memory evolution and conflict labeling for the same entity.

Multi-tier memory system for AI assistants, integrating semantic, episodic, time-series, and spatial memory with pattern detection and MCP tools.

Self-hosted personal knowledge graph for Claude that persists across sessions, devices, and tools. Built on Neo4j with local semantic embeddings; OAuth 2.1 lets Claude Code, Claude Desktop, and claude.ai web all hit the same graph.

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.

An MCP server that provides persistent memory capabilities for AI agents using Mem0, enabling storage, search, and management of contextual information across conversations with support for multiple backends and LLM providers.

A tool for detecting and cleaning Java memory shells via local or SSH remote execution. It enables AI agents to scan Java processes, analyze suspicious class code, and safely remove memory shells after user confirmation.

A persistent world your agents share across sessions and models. MCP memory server with semantic memory retrieval, cross-agent handoff, a hosted remote endpoint with OAuth, a free 24-hour room, and an open-source local stdio server.

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

Provides AI-driven project memory management through structured prompts that help Claude parse tasks from specs, review code changes, sync with commit history, and maintain project documentation without directly accessing files.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

Enables AI agents to maintain long-term, cross-session memory by extracting facts, reconciling state conflicts, and retrieving relevant memories via vector search.

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.