"Managing and Working with Files" matching MCP servers:

Provides secure, sandboxed filesystem operations including reading, writing, listing, searching, and managing files and directories within a configurable working directory with strict security controls.

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

Enables AI assistants to inspect, create, and report on IFC/BIM files locally, and to open models in a viewer with BCF viewpoint support.

Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.

Enables LLM agents to find and safely delete duplicate files using content-based detection, with smart copy prioritization and dry-run mode.

A plain-files brain template and MCP server that lets models read owned, portable working memory via list, read, and grep-style search tools.

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 AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

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.

MCP server for parsing .eml email files, extracting metadata, content, and attachments with smart organization into folders. Enables AI to read and handle email files offline without triggering trackers.

Read selected local folders from ChatGPT on macOS, with per-folder read-only or read-write access and hash-checked, recoverable edits. Requires local installation and a private ChatGPT app. The Glama container is a synthetic evaluation demo; it does not connect to files on your Mac.

Enables downloading real binary files from Egnyte and uploading large files with chunked support, complementing the official Egnyte MCP connector.

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

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

A convention-aware MCP server for managing markdown files with YAML schema validation. It enables AI agents to read, write, search, and validate markdown notes while enforcing user-defined conventions across directories like Obsidian vaults and documentation repositories.

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

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

MCP server for bulk-creating files and folders for any project, with built-in templates and custom scaffold support.

An MCP server for managing Rails-style localization files (YAML/JSON), enabling coding agents to read, search, write, and audit translations without hand-editing files.