"Access to filesystem resources" matching MCP servers:

An MCP server that gives AI agents access to configured databases (PostgreSQL, MySQL, Redshift, SQL Server) with SSH/AWS SSM tunnels, pluggable secret providers, and strict per-instance isolation.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables secure filesystem operations with directory sandboxing and optional read-only mode. Supports file reading/writing, directory management, file searching, and text operations while restricting access to specified directories.

Enables AI clients like Claude to read and manage Microsoft To Do task lists and tasks via the Microsoft Graph API, running locally over stdio with secure token storage.

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 querying the Global Solo Banking Access Index to check which US business banking providers explicitly accept, restrict, or remain silent on applicants from 8 countries, with dated evidence URLs and provenance metadata.

MCP Server that enables LLMs to interact with the local filesystem.

A secure, highly capable MCP server written in Rust. It exposes a comprehensive suite of filesystem operations as tools for AI agents.

Provides filesystem, web search, SQLite, and system tools for AI assistants like Claude, enabling secure access to local resources and the web.

Enables AI coding agents to watch directories for live filesystem changes (create, modify, delete, move) via the Model Context Protocol, providing event-driven access without busy-polling.

A Model Context Protocol server that provides AI agents with secure access to local filesystem operations, enabling reading, writing, and managing files through a standardized interface.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

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.

A secure Model Context Protocol server that provides controlled filesystem access within predefined directories, enabling AI models to perform file and directory operations with strict path validation.

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.

Provides LLM-optimized filesystem access with intelligent file pagination for large files, lightning-fast ripgrep-powered code search with regex support, and security sandboxing to safely explore and search codebases.

Enables AI agents to understand, inspect, create, validate, build, and document Jekyll component frameworks through Jekyll-aware tools, resources, prompts, sandboxed filesystem access, and configurable write modes.

Node.js server implementing Model Context Protocol (MCP) for filesystem operations.

Exposes Linux filesystem operations as tools for LLM agents, with configurable root directory and read-only mode, built with FastMCP.

Provides AI agents with direct filesystem access to an Obsidian vault for note management, task orchestration, context persistence, and git synchronization.