MCP File System Server

@asirulnik

Repository

Basic information

About MCP File System Server

No overview available yet

#mcp #file-system #server #ai-assistant

MCP File System Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp_server_filesystem_01": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP File System Server tools

Lists files and directories in the project directory

Reads the contents of a file

Creates or overwrites files atomically

Adds content to existing files

Removes files from the filesystem

Makes selective edits using pattern matching

Overview

What is MCP File System Server?

MCP File System Server is a Model Context Protocol server that enables AI assistants (via Claude Desktop, VSCode/Cline extension, or other MCP-compatible systems) to perform file system operations—read, write, edit, delete—within a specified project directory. It is built for developers who want to collaborate with AI on local codebases through natural-language prompts.

How to use MCP File System Server?

Install the server by cloning the repository and running pip install -e . inside its directory. Then launch it with python -m src.main --project-dir /path/to/project, optionally setting --log-level and --log-file. Add the server’s configuration to your MCP client’s settings (e.g., Claude Desktop’s claude_desktop_config.json or Cline’s cline_mcp_settings.json) and restart the client.

Key features of MCP File System Server

list_directory: list files and directories in the project directory
read_file: read the contents of a file
save_file: atomically create or overwrite files with content
append_file: append content to an existing file
delete_this_file: permanently delete a file from the filesystem
edit_file: make selective edits using pattern matching with diff preview

Use cases of MCP File System Server

AI-assisted code review and analysis of existing project files
Generating and writing new files (e.g., scaffolding, configuration) based on natural-language descriptions
Making targeted edits to source code without rewriting entire files
Debugging and fixing issues by reading, analyzing, and updating code
Building complete implementations from specifications through iterative prompting

Frequently asked questions

What operations does the server support?

It supports six tools: `list_directory`, `read_file`, `save_file`, `append_file`, `delete_this_file`, and `edit_file` (which offers line-based pattern matching and dry-run previews).

What are the runtime requirements?

Python 3 (with a virtual environment recommended) and the dependencies installed via `pip install -e .`. The server uses FastMCP and can be run on Windows, macOS, or Linux.

Where are logs stored, and how are they formatted?

Standard human-readable logs go to the console. Optionally, structured JSON logs can be written to a file specified with `--log-file`. Log level is configurable (DEBUG, INFO, WARNING, ERROR, CRITICAL).

How does the server ensure security?

All file paths are normalized and validated to stay within the project directory; path traversal attacks are blocked. Files are written atomically to prevent data corruption, and the `--project-dir` argument is required.

What transports and authentication are supported?

The server communicates via MCP’s standard transport (stdin/stdout) used by Claude Desktop and Cline. No external API endpoints or authentication are mentioned—access is governed by the MCP client’s auto-approval settings.