"Understanding Cursor or Cline Context in Long-term Memory Systems" matching MCP servers:

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.

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.

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.

An MCP server for managing and activating persona templates and components by writing to .clinerules files, supporting version tracking and file-based storage.

Enables AI coding agents to persist structured long-term memory (gotchas, architecture, API notes) in a .context folder and sync across devices and agents via Git.

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.

MCP server that gives AI chat real vision by reading images, files, logs, and zip archives via local OCR in any language, with privacy-first processing.

MCP server providing lossless file reads with deduplication, per-repo token metering, and HMAC-signed context receipts. Enables auditable, vendor-neutral measurement of what an AI agent saw.

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.

Provides LLMs with secure, read-only access to local documentation by scanning directories, extracting content from PDF, DOCX, Markdown, and text files, and performing keyword searches.

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.

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

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

A unified context layer that connects your local data — repositories, documents, remote machines, and notes — to LLM interfaces through the Model Context Protocol (MCP).

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.

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.

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