"File system requirements: mounted directory, persistent state, and full R/W access" matching MCP servers:

Provides full access to a local Windows computer via MCP, enabling arbitrary command execution, file operations, and process management through a secure stdio or HTTP tunnel.

A comprehensive MCP (Model Context Protocol) server for file system operations, providing Claude and other AI assistants with access to local files and directories.

Enables agents and devices to discover, inspect, and invoke filesystem operations on explicitly allowed directories across the DreamMate capability network, including reading, writing, editing, listing, searching, moving, and metadata inspection. It also supports native MCP clients, HTTP invocation, read-only restrictions, and service reporting to a local gateway.

Provides secure file read and write operations within a sandboxed directory, allowing AI assistants to safely create, modify, and access files without risk of accessing the broader file system.

A secure, sandboxed file system server that enables reading, writing, searching, and managing files through MCP-compatible AI clients with path traversal protection and size limits.

An agentic file-system assistant that lets users read, write, list, and search local files through natural language, using a LangChain agent with an Ollama LLM backed by a FastMCP server.

Provides AI assistants with semantic search and read access to local files and directories, enabling knowledge retrieval from indexed content.

Enables comprehensive directory analysis and file management operations including project structure exploration, intelligent file search, full CRUD operations on files and directories, batch operations with rollback capabilities, and Git integration.

Windows-first MCP server for deterministic file writes with atomic create, replace, and structured edit operations, preserving encoding and newline styles.

Deep directory tree visualization tool enabling efficient visualization of complex directory structures with AI-powered analysis capabilities.

A server implementing the Model Context Protocol that provides filesystem operations (read/write, directory management, file movement) through a standardized interface with security controls for allowed directories.

An MCP server that provides a flexible lens into directory structures and files, enabling LLM clients to efficiently navigate and understand codebases with minimal noise. It offers secure, gitignore-aware file access with tools like directory listing, file reading, and grep-like search.

An MCP server that gives AI agents file system access: read, write, search, hash, directory trees — 12 tools, zero dependencies, pure Python stdlib.

MCP server enabling AI assistants to securely operate remote servers via persistent SSH sessions, with tools for command execution, file transfer, directory listing, and system monitoring.

Turns any Linux server into an AI-agent-accessible machine over HTTPS, allowing MCP clients like ChatGPT, Claude, and Grok to securely control files, run shell commands, inspect system state, query SQLite, and work with git behind a bearer token.

Enables safe file system operations including reading, writing, updating, and deleting files with built-in security safeguards, automatic backups, and comprehensive error handling. Provides directory listing, file metadata extraction, and protects against operations on system-critical paths.

Provides file system access for resume matching through JSON-RPC, enabling semantic search and workflow orchestration with LangGraph.

Educational MCP server for basic file operations (read/write) via the Model Context Protocol.

A Model Context Protocol server that provides secure, sandboxed file system operations including reading, writing, and managing files within a configurable base directory. It features robust path traversal protection to ensure all file interactions remain confined to a safe, restricted environment.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.