"file system" matching MCP servers:

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

A powerful context management system that maintains persistent context across coding sessions, helping development teams track project structure, dependencies, and progress.

MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.

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

A zero-dependency, file-based persistent memory system for AI agents with tiered memory, Ebbinghaus decay, and keyword retrieval.

An MCP server implementation that enables interaction with the Letta API for managing agents, memory blocks, and tools in the Letta system.

A personal knowledge management system built on the Model Context Protocol that transforms daily notes into organized, searchable knowledge.

About Your task manager is the best agent memory you're not using. An agent-native context layer over your existing task app.

Scalable, high-performance knowledge graph memory system with semantic search, temporal awareness, and advanced relation management.

A comprehensive Model Context Protocol (MCP) server for Obsidian on macOS. It provides extensive tools for interacting with Obsidian vaults, notes, and application state through AppleScript, URI schemes, and direct file system access.

Captures and retrieves Markdown records for a personal recording system, enabling journaling, input tracking, search, and date-range review.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

Enables AI assistants to interact with TheBrain's knowledge management system for creating, searching, and organizing thoughts, notes, and attachments using natural language. It provides comprehensive tools for managing hierarchical thought structures, link relationships, and file attachments through TheBrain's API.

An MCP server that provides searchable local storage for Claude conversation history, featuring automatic topic extraction and weekly insight summaries. It enables Claude to retrieve context from past sessions through full-text search and organized file storage.

A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.

Provides a structured documentation system for context preservation in AI assistant environments, helping users create and manage memory banks for their projects.

Local-first knowledge system for reasoning agents, exposing facts, evidence, documents, retrieval, and audit history through a thin stdio MCP server.

An automated system that processes raw text through a three-stage pipeline to assess data quality, enhance information, and generate structured knowledge graphs. It provides tools for triple extraction with confidence scoring and creates interactive HTML visualizations of the resulting graph.

Enterprise MCP server with memory management, API key control, and system health tools, ready for Claude integration with Supabase.

A Model Context Protocol server implementation that provides a standardized interface for interacting with Smallest.ai's knowledge base management system.