"Memory" matching MCP servers:

Provides a local markdown-based memory system for coding agents through MCP, enabling search, add, register, inventory, sync, and ingest operations across user and project memory. It gives any agent tool a durable, provider-agnostic shared memory stored in folders you own.

MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.

Provides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.

A local MCP server that provides agents with tools to list, read, search, inspect history and diffs, and capture unstructured text in a user-owned Git repository of durable memory.

Provides project memory management for Claude Desktop, storing memories as Markdown files with intelligent keyword-based retrieval and automatic creation/update decisions by LLM.

Enables reading, writing, and searching a local markdown-based memory store using MCP tools, with safety checks and index consistency.

Enables AI clients to preserve and share knowledge as plain Markdown files in a local folder the user owns, with tools to remember, recall, get, update, forget, and list scopes. Memories are stored by scope, versioned rather than overwritten, and readable or editable in Obsidian or any text editor.

Enables Claude Code to persist and recall cross-repository memories as Markdown files via save, search, read, and health-check tools, with local-only storage and no cloud services.

A local-first, Markdown-native AI agent layered memory system that provides MCP tools for storing, recalling, exporting, and importing memories with types like working, persona, and fact.

Exposes local memory vaults as 6 MCP tools over stdio, enabling clients like Windsurf, Zed, and Claude Desktop to read and write memory.

A local-first shared memory layer for MCP-aware agents like Claude, Codex, and Hermes, enabling persistent memory across chats and clients via Markdown files and SQLite FTS.

A local MCP server that stores user-approved corrections, preferences, and reusable criteria in plain Markdown files, with separate global and project memory. It provides tools to list, search, and retrieve relevant criteria to help agents avoid repeating mistakes.

A Model Context Protocol server that enables Claude to persistently store, search, and manage text memories with tags in a local JSON file.

MCP server for agent-maintained memories, allowing creation, reading, updating, deletion, and listing of memories with global or repo scopes.

Enables stdio-capable MCP hosts to store and retrieve memories in a caller-specified private directory, keeping program repositories separate from memory data.

A self-hosted memory layer for Claude using plain markdown files, enabling persistent context across different Claude accounts.

Provides tools for AI agents to manage long-term memories, daily notes, and TODO lists through a structured markdown file system. It enables context awareness by allowing agents to read, write, and search entries for persistent information storage.

Description: Persistent local memory for Claude, Cursor and Codex. 13 MCP tools, SQLite + FTS5 + Knowledge Graph. No cloud, no API keys. One command: npx @studiomeyer/local-memory-mcp.

Provides eight scoped, read-only tools for health checks and for finding, searching, reading, listing, traversing, grepping, and globbing a configured user's native memories and personal-context subtree, without exposing capture or write operations.

MCP server for structured reflection and self-modeling over Everlog diary exports, enabling agents to query local diary evidence and maintain versioned artifacts of threads, moments, beliefs, and decisions.

A memory, docs, and repo context layer for engineering agents, providing typed persistent memory, RAG document retrieval, and repository-aware tools to recall decisions, runbooks, and operational knowledge across sessions.

Enables AI tools like GitHub Copilot to manage and persist context using a local JSON-based memory store. Provides CLI, MCP server, and VS Code integration for storing, retrieving, and managing context entries.

Exposes read-only local markdown envelopes through MCP tools for health, context, and recall queries.

Local-first, file-based memory layer for AI agents — one shared Markdown vault across Claude, Codex, Gemini, Cursor and any MCP client. Provides read/write memory tools with an audit trail, per-agent trust levels, and Git sync; no cloud and no lock-in.

Exposes local persistent memory as an MCP server with Markdown storage, PARA organization, Zettelkasten linking, and SQLite FTS5 search. Enables Claude and other MCP-compatible agents to store, organize, and retrieve knowledge with context-based recommendations through the Olima association engine.

Bridges Claude Code and Claude.ai by exposing project memory files over MCP for shared context across both interfaces.

An MCP server that gives AI models a persistent notebook backed by a folder of Markdown files, with tools to discover, read, write, edit, and delete notes.

A local-first MCP server that gives AI coding assistants persistent, structured, human-readable memory for a software project by storing project knowledge as Markdown files in the project's .dev-context-memory/ folder.

为Kimi Code CLI提供持久化记忆系统，支持文件学习、智能检索和混合存储，让大模型拥有长效记忆能力。

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.