Python (MCP) Filesystem Server

Name: Python (MCP) Filesystem Server
Author: hypercat

@hypercat

关于 Python (MCP) Filesystem Server

This is a robust Python-based MCP Filesystem Server. It enables AI models and applications to securely interact with the host system's file directories through a defined set of tools, allowing for operations like reading, writing, moving, and listing files and directories.

#filesystem #python #mcp

基本信息

分类

文件与存储

运行时

python

传输方式

stdio

发布者

hypercat

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "PyMCP-FS": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-r",
        "pyproject.toml"
      ]
    }
  }
}

工具

未检测到工具

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概览

What is Python (MCP) Filesystem Server?

Python (MCP) Filesystem Server is a Python-based Model Context Protocol (MCP) server that enables AI models and applications to securely interact with host file directories via a defined set of tools. It uses the fastmcp library and confines all file operations to a configurable list of allowed directories.

How to use Python (MCP) Filesystem Server?

Clone the repository and initialize with uv pip install -r pyproject.toml. Run python3 main.py -d /path/to/allowed/dir1 /path/to/another/allowed/dir2 [--log-level LEVEL] [--log-file PATH]. The server listens for MCP messages on stdin and responds on stdout. A test script (test_mcp_server.py) is provided to verify functionality.

Key features of Python (MCP) Filesystem Server

Strict confinement to predefined allowed directories.
Tools for reading, writing, editing, moving, and listing files.
Recursive directory tree generation.
Configurable logging with file rotation.
Symlink validation to prevent path escape.

Use cases of Python (MCP) Filesystem Server

Allowing an AI assistant to read and edit source code in a project directory.
Enabling a chatbot to manage user-uploaded files (e.g., drafts, notes).
Providing controlled filesystem access for automated reporting or data processing tools.
Letting an AI model safely list and inspect files within a sandboxed workspace.