mini_mcp is an MCP server that provides an interface to list files and folders on a macOS user's desktop. Built using FastMCP, it connects AI client applications directly to the local macOS filesystem environment to inspect desktop contents. Developers and desktop users who run AI assistants such as Claude Desktop or Cursor can use this tool to allow models to survey desktop workspaces programmatically. The server exposes a dedicated function named list_desktop_files, which queries the local user's ~/Desktop directory and returns an array of file and folder names. This enables models to identify available documents, screenshots, and directories before deciding on subsequent operational steps or helping users manage cluttered workspaces. It operates locally using a standard Python runtime environment, maintaining a minimal footprint and simple project architecture with no complex external server infrastructure.
Category: Files, Documents & PDFs
Tags: desktop, file-management, filesystem, macos
bash conda create -n mcp python=3.12 conda activate mcp pip install fastmcp Alternatively, install dependencies using: bash pip install -r requirements.txt 2. Add the server to your MCP client configuration (such as Claude Desktop or Cursor): json { "mcpServers": { "list_desktop_files": { "command": "/Users/hzq/anaconda/anaconda3/envs/mcp/bin/python", "args": [ "/Users/hzq/py_projects/mini_mcp/main.py" ] } } } 3. Update the file paths in the configuration to match the absolute path of your local Python interpreter and your main.py script.Part of MCP Servers
mini_mcp is a lightweight Model Context Protocol server built with FastMCP. It exposes a single tool to allow AI assistants to list all files and directories residing on the current macOS desktop.
mini_mcp is designed specifically for macOS because it targets the ~/Desktop directory structure. Running it on Windows or Linux requires manually editing the path definition inside the main.py file to match the target operating system.
It provides a tool called list_desktop_files. When invoked by an external MCP client, it inspects the desktop directory and returns an array of strings representing file and folder names.
You configure it under the mcpServers key in your client settings. Specify the path to your Python interpreter under command and pass the full path to main.py within the args array.