"Files" matching MCP servers:

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

A lightweight MCP server for basic file operations, enabling reading, writing, and listing files securely via the Model Context Protocol.

Enables reading, writing, appending, and listing files, restricted to explicitly allowed directories with safety checks against path traversal and symlink escapes.

A safe MCP server for sandboxed filesystem operations (list, move, create directories, delete files) via pure Python, designed for Claude Desktop.

Enables accessing and managing files from configured folders with filtering and size limits, allowing listing, reading, and searching files via MCP tools and resources.

Enables listing, reading, and searching local files and directories through MCP tools.

A secure, read-only MCP server for browsing and searching files in a specified directory with path traversal protection and .gitignore support.

Enables AI models to perform file operations, user management, automations, and more within Files.com's secure file transfer platform via the Model Context Protocol.

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 AI assistants to load and query local GEDCOM genealogy files, supporting search, browsing, and family tree traversal.

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.

Analyzes Python project structure by exploring directory trees, extracting outlines from Python and Markdown files, and inspecting OpenAPI specifications.

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.

Anonymizes documents via the Stript desktop app locally, ensuring personal data never enters the conversation. Provides tools to anonymize files and clipboard content, fetch results, and restore original values to local files.

MCP server that analyzes codebases with tree-sitter and generates AGENTS.md files for AI agents.

Navigate, search, and edit large codebases, logs, and data files that exceed AI context limits.

Provides tools to encode files to Base64 strings and decode Base64 content back to files, supporting both text and binary formats.

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.