"Applications or tools with full local file system 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.

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.

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.

Enables cloud services with MCP support, such as Notion AI, to read, search, edit, create, and delete files within a single designated folder on your computer, and to run only allowed commands.

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.

Enables local MCP-assisted processing of Access database tables, HTML5 advertising ZIP image assets, layered PDFs, and ONIX book-update requests through RapidAPI. It saves results in a selected workspace folder while requiring explicit consent for each processing call.

MCP server for file operations with non-UTF-8/Unicode encoding: Cyrillic, CP1251, CP1252, ISO-8859, KOI8 auto-detection

Enables AI agents to explore, analyze, and search file systems, with tools for directory trees, file statistics, duplicate detection, code counting, and multi-criteria file search.

Adds workspace-scoped copy, move, and delete tools to DevSpace so filesystem changes are validated against workspace boundaries and protected paths instead of relying on shell cp, mv, or rm commands.

A Model Context Protocol (MCP) server that allows AI models to safely access and interact with local file systems, enabling reading file contents, listing directories, and retrieving file metadata.

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.

Provides tools for searching and reading local files, supporting metadata filters, PDF full-text keyword search, and sandboxed file access.

Enables orchestrating models to delegate reading and answering questions about local files to a local LLM, avoiding sending file contents through the orchestrator's context.

Provides tools to check disk usage and search files by keyword on the local system.

Provides secure file read, write, and edit operations for Windows, with enterprise-grade features like atomic writes, file locking, and path validation.

Local-first filesystem MCP bridge with ripgrep search, atomic writes, multiple transports

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

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.

Enables AI models to perform file system operations (reading, creating, and listing files) on a local file system through a standardized Model Context Protocol interface.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

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

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.

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.

Enables uploading local files to Slack with a message, supporting channels, DMs, threads, and file titles.

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.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Enables agents to perform workspace-scoped file deletion through a ticket-gated workflow: preview paths and risks, move approved files into a recoverable .del batch, then permanently purge them after confirmation.

An MCP server that exposes filesystem operations — listing directories, reading, writing, and searching files — as tools an LLM can discover and invoke at runtime.