What are the required dependencies?
FastMCP, Pydantic, and platform-specific libraries: pywin32 and WMI on Windows only.
@MCP-Mirror
基本信息
Mirror of
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"calebmwelsh_file-system-mcp-server": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
It's a file system management server built with FastMCP that provides a comprehensive set of tools for file and directory operations. Designed for integration with AI assistants like Claude, it enables automated file management through a structured API.
Clone the repository, create a virtual environment, and install dependencies with pip install -r requirements.txt. For Claude integration, add the server to claude_desktop_config.json using the absolute paths to your Python executable and the fs_server.py script.
FastMCP, Pydantic, and platform-specific libraries: pywin32 and WMI on Windows only.
Add a entry to `claude_desktop_config.json` with the `command` pointing to your Python executable and `args` containing the path to `fs_server.py`. Example for Windows: `"command": "C:\\Users\\YourUsername\\...\\python.exe"`, `"args": ["C:\\Users\\...\\fs_server.py"]`.
The `delete_file` function may fail in some cases, and `list_drives` may not detect all drives correctly. Windows-specific features are unavailable on macOS/Linux.
Collections are stored in a user-specified directory. If no location is given, they default to `data/collections` within the project folder.
Yes, basic file and directory operations are supported. Windows-specific features (drive listing, special folders, detailed system info) are not available on macOS/Linux.
Markdown To PDF Conversion MCP

Upload once. Find, use and share across your AI workflows. drop.media is one media library for you and every AI agent you use: files added from Claude, ChatGPT, Cursor, the terminal or the web can be found, reused and sh
A Model Context Protocol (MCP) server that provides file system context to Large Language Models (LLMs). This server enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.
📄 The PDF intelligence layer for AI agents — Agent Document Twin, evidence-first extraction, visual crops, OCR provenance, trust reports, and benchmark-gated releases. MCP server for Claude, Cursor, VS Code, and any MCP client.
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