"memory" matching MCP servers:

Enables MCP-capable coding agents to semantically search, store, and inspect a single local, cross-tool index of session histories and project docs. Agents can retrieve what other tools and prior sessions already discovered.

Gives every AI agent on a machine a shared, local-first long-term memory: 16 tools to save, search, edit and organize structured notes in one SQLite file, with attribution per client. Runs over stdio or localhost HTTP, so Claude Code, omp and any other MCP client recall the same facts, decisions and entities.

Lets any MCP-capable agent look up and extend a shared local store of entities, relations and facts about the user — people, projects, places, channels — resolving free phrases to cards and searching past conversations by words and by meaning.

Enables AI assistants to retain, review, approve, and retrieve encrypted local notes, decisions, preferences, and follow-ups across sessions, with retained source evidence and correction history.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Enables AI assistants to maintain a persistent, local memory using SQLite with ranked full-text search, German morphological matching, and two-axis filing, all without external services.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.

A notes app that becomes your second brain. Open source, private, encrypted when you want it, and every file stays yours. Mac, Windows, Linux and self host!

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

Local-first personal memory for AI agents. Ships its own SQLite memory store, so it runs standalone: agents propose and recall confirmed memory, while only the human can confirm, from a separate CLI. Optionally uses the macOS Hive app for encrypted vaults. Also provides a shared board for coordinating several agents.

A local-first MCP server that exposes personal notes and files as unified semantic context for AI agents via vector search and file monitoring.

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.

Enables multiple AI agents on one machine to write, search, fetch, link, and give feedback on a shared local store of Markdown-backed facts, preferences, and conventions that persists across sessions. Memories gain confidence as different hosts confirm their use and can be distilled into denser ones, so agents stop re-discovering the same context.

Long-term memory for AI coding agents, stored as a tree of plain local files. Agents search it before answering and save what lasts; changed facts are kept as history and flagged as outdated.

Project Memory stores decisions, evidence, outcomes and reviewed lessons in local SQLite. Assistants retrieve bounded context through three MCP tools. People follow and plan work in a live workspace with an overview, sprint board, decision history, readable documents, skills and project maps. Offline exports remain available.

A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep

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.

An MCP server that implements memory with decay mechanics, allowing AI agents to store and retrieve memories that fade over time unless accessed, with a permanent journal for verification.

Automatically records AI conversation turns and code changes to local Markdown files to provide persistent context across chat sessions. It enables AI agents to search history through MCP tools and provides a web viewer for browsing past discussions.