"filesystem" matching MCP servers:

Provides advanced filesystem operations for AI-assisted development, including batch file reading, renaming, moving, project structure display, and command execution with Python virtual environment auto-activation.

An enhanced Model Context Protocol filesystem server that fixes common limitations and adds features like glob pattern search, head/tail reading, intelligent file editing with syntax validation, and new tools for delete and command execution.

Enables comprehensive filesystem operations across Linux, macOS, and Windows with platform-aware command execution, secure path restrictions, and intelligent adaptations for file search, directory management, and shell commands specific to each operating system.

Enables exploration and search of local filesystems using glob pattern matching to find files and grep to search for text patterns within files.

MCP server that vets LLM-emitted shell commands BEFORE execution — detects rm -rf nested deep in chains, package-manager glob removal (apt remove 'nvidia'), dd/mkfs filesystem destruction, chmod 777 / chown -R privilege blast, network-exfil via curl | bash, chained shutdown/reboot, git destructive ops. 30 detection rules across 8 families. Sub-second, local, free, MCP-native.

MCP server that gives Claude Desktop and other desktop MCP clients filesystem powers—read, write, edit, and manage files like AI coding assistants.

Give Claude Desktop terminal, filesystem, and background-job access on your local Linux machine. Zero-dependency MCP extension, MIT-licensed.

Lets Claude Code drive a Qodalis CLI server, exposing that server's CLI commands, filesystem, data explorer, jobs, and plugin tools with the configured account's permissions. It handles token or password sign-in, automatic reconnection after drops, read-only filtering, and client-side allow/deny lists.

Enables executing local commands via an argv-based tool with optional non-interactive sudo, command allowlisting, and filesystem write confinement using Bubblewrap.

Provides LLMs with local filesystem operations (read/write files, list directories) and command execution via MCP, enabling file management and task automation within AI clients.

Sandboxed bash execution MCP server for AI agents, using an in-memory virtual filesystem overlay to prevent real filesystem damage, with configurable network access, timeouts, and optional Python/JS runtimes.

Provides core filesystem, shell, search, and listing tools with a path sandbox, supporting HTTP and stdio transports.

Enables MCP clients such as Claude and Cursor to control an isolated cloud machine with a real browser, shell, filesystem, and web access, so agents can navigate pages, click and type, run commands, manage files, and search or fetch web content.

An MCP server for ROS 2 development that enables controlled creation of workspaces, packages, nodes, launch files, and tests within a sandboxed directory, with secure filesystem boundaries.

Enables management of Sprite VMs through interactive dashboards and terminal interfaces. It allows users to execute commands, create filesystem snapshots, transfer files, and manage VM lifecycles via natural language.

A comprehensive MCP tools collection providing filesystem operations, command execution, system tools, and more, with cross-platform support and strong security features.

Enables MCP-capable AI clients to control a local computer over stdio with filesystem operations, ripgrep search, shell command execution, and persistent process sessions.

This server enables AI agents to execute terminal commands, manage running processes, and interact with the host's filesystem and system configuration. It supports complex operations such as code execution, file searching, and surgical data editing.

Enables MCP clients on macOS to perform bounded read-only filesystem operations and a narrow allowlist of process diagnostics over STDIO or authenticated loopback Streamable HTTP. It excludes file writes, arbitrary shell access, GUI/browser automation, and remote relay.

AI agent file editing via MCP: JSON/YAML/TOML, AST renames, markdown, batch.

A beginner-friendly MCP server that enables AI to explore file systems through tools for listing directories, reading files, searching with wildcards, and getting file metadata. Perfect for learning MCP development while providing practical file system interaction capabilities.

Comprehensive MCP server for filesystem operations, process management, interactive sessions, and async file search. Includes utilities for JSON repair, encoding fixes, duplicate detection, OCR, ZIP archives, and Markdown export.

Enables MCP clients to securely connect to a paired Windows machine through a self-hosted Cloudflare relay and use its local filesystem and command-execution tools over Streamable HTTP and WebSocket.

Local macOS MCP bridge that gives ChatGPT shell, unrestricted filesystem access, real PTY sessions, background jobs, and read-only stored Codex history. ChatGPT stays the reasoning layer; the bridge makes no model calls.

Enables an MCP client to start and drive terminal processes, read and write files, make exact-match text edits, move files, inspect metadata, and paginate through local file-content searches. It also exposes configuration, prompt, usage and recent-call tools alongside those filesystem, search and process capabilities.

A local AI agent system that gives any LLM real access to the filesystem, terminal, and codebase via MCP, usable as a standalone terminal agent or Continue.dev integration in VS Code.

A filesystem MCP server that journals every file operation (write, delete, move, mkdir) and outbound commands (exec, http) into an append-only ledger, enabling undo and compensation of actions.

Enables MCP clients to spawn and control Codex CLI and Claude Code sessions on the host machine, with session management and filesystem access.

Enables clients to connect to Gemini, local Ollama models, terminal commands, and a restricted filesystem server through generated Codex and Claude Desktop configurations.

Enables terminal and filesystem capabilities through local stdio or remote device modes, backed by a contract and validation layer.

Execute scientific scripts (R, Python, GMT, LaTeX, Octave, Julia, etc.) in isolated, disposable containers with no host filesystem access.

Enables AI assistants to operate and monitor Windows workspaces through native tools for filesystem operations, PowerShell execution, background tasks, Windows services, GPU telemetry, PDF generation, and a built-in web gateway/dashboard.

Enables AI agents to safely work on Windows developer workstations through governed, project-scoped filesystem access, durable command execution, bounded search, Windows operations, and resource-aware runtime controls. It also supports optional developer-context backends for code navigation, repository graph exploration, and memory retrieval.

Enables ChatGPT and Claude to access your desktop's filesystem and terminal via Desktop Commander over HTTPS with OAuth 2.1 authentication.

Enables users to manage Linux HPC clusters from ChatGPT via an outbound Secure MCP Tunnel, with read-only and opt-in filesystem, command execution, background process, and Slurm/PBS scheduler tools.

Exposes a read-only virtual filesystem over MCP so agents can explore documentation with real shell commands (ls, cat, grep, head, sed) answered from a vector store rather than a disk or sandbox. It also provides a hybrid dense-vector plus BM25 search tool for finding where to look first, with page access governed by group rules.

Local automation bridge that is both an MCP server and client: 234 tools across 44 namespaces for shell, filesystem, git, desktop control, browser (CDP), Android (ADB), OCR/ASR and memory, plus the ability to connect external MCP servers. Sandboxed execution with token auth, fail-closed policy and audit log.

Enables AI assistants to introspect a Laravel application's routes, models, controllers, migrations, and more through the Model Context Protocol, running locally via php artisan commands and filesystem scanning.

A stateless MCP server for filesystem operations, command execution, and computation, designed for use with llama.cpp WebUI.

A Model Context Protocol (MCP) server that provides VSCode context and filesystem operations for AI assistants.