"Understanding Persistent Memory in Cursor Functionality" matching MCP servers:

A persistent SQLite-backed storage server that enables Cursor IDE's AI assistant to remember information across sessions with global or project-specific scopes. It supports complete CRUD operations, tag-based organization, and keyword search to manage user preferences and context effectively.

MCP server providing filesystem allowlist and pack-aware Qdrant RAG search. Enables reading files, listing directories, and performing filtered RAG searches with case and pack IDs.

An MCP server that enables AI agents to create, read, edit, and manage Jupyter Notebook files programmatically, overcoming limitations in Cursor's native notebook support.

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 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.

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-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 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.

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.

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

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.

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

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.

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.

MCP server for Obsidian vaults, optimised for Cursor agents — safe note editing, lean tool surface, direct filesystem access.

Automatically organizes files in your Downloads folder by categorizing them into appropriate directories based on file types.

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.