"Information about file systems" matching MCP servers:

A sophisticated MCP server providing powerful file search capabilities including single file search, recursive directory search, and file information retrieval.

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.

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.

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

A secure file server for AI assistants that provides comprehensive file operations and text manipulation with configurable access levels and multiple connection modes.

Enables file extraction, organization, and GitHub repository management through MCP tools, allowing AI agents to copy/move files, delete repositories, and automate workflows.

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.

A beginner MCP server that enables Claude to read local text, CSV, and Markdown files. Built as a learning project to understand how to connect AI to local file systems using the MCP protocol.

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

Enables users to ask natural-language questions about a local folder's contents, including file names, sizes, and timestamps, with rollups by type and age and cleanup suggestions for stale or large files. It returns metadata only and cannot read, move, or delete files.

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.

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

A personal file-indexing MCP server that provides semantic and keyword search over a file index, plus file content lookup and browsing. It enables agents to search and retrieve files from a user's home directory.

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 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 agents to read and extract text, tables, and image content from files (PDF, DOCX, PPTX, SVG, PNG) within a folder, providing structured data for interpretation by the calling model.