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FileSystem MCP Server

by Oncorporationversion 0.1.4i★ –iRuns on your computer
Registry nameio.github.Oncorporation/filesystem-server

Install

Overview

Description from the maker (original English)

Secure filesystem access for AI agents with configurable directory and file type restrictions

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "filesystem": {
      "command": "uvx",
      "args": [
        "vs-filesystem-mcp-server"
      ]
    }
  }
}

Run this in your terminal

claude mcp add filesystem -- uvx vs-filesystem-mcp-server

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "filesystem": {
      "command": "uvx",
      "args": [
        "vs-filesystem-mcp-server"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "filesystem": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "vs-filesystem-mcp-server"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Oncorporation, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32655 servers in this category
  • Published to the registry more recently than 61% of the other 32655 servers in this category
  • Basic checks equal to or better than 100% of the other 32655 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is FileSystem MCP Server safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.4) reached the registry 24 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, SuperCollider

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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Make sound with SuperCollider: synths, drums, chords, melodies and soundscapes over OSC.

Runs on your computerUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

FileSystem MCP Server

Version: 0.1.4 — Last updated: 2026-10-13

Local MCP server for Visual Studio 2022+ that provides code-workspace functionality by giving AI agents selective access to project folders and files

Table of Contents

  • 🎯 Target Environment
  • Features
  • Installation
  • Quick Start
  • Configuration Options
  • Option 1: Config.json File (Simplest - Recommended for Beginners)
  • Option 2: Command-Line Arguments (Advanced - For MCP Clients)
  • Option 3: Hybrid Approach (Best of Both Worlds)
  • Usage
  • Command Line Examples
  • Available Tools
  • Why This Hybrid Approach is Perfect
  • Visual Studio 2022+ Debugging
  • Visual Studio 2022+ Usage Examples
  • Editing Your mcp.json File via GitHub Copilot Chat
  • Security
  • Error Handling
  • Troubleshooting
  • MCP Configuration Issues
  • Visual Studio 2022+ Debugging
  • Common Issues
  • Command Line Reference
  • Cross-Platform Path Support
  • Advanced & Real-World MCP Configuration Examples

🎯 Target Environment

This MCP server is optimized for:

  • Visual Studio 2022+ development workflows
  • Local development environments without complex workspace setups
  • Direct folder access scenarios where you need filesystem operations
  • Development environments that don't use `.code-workspace` files
  • Individual project directories rather than multi-root workspaces

Features

  • Directory Traversal: List contents of allowed directories
  • File Reading: Read contents of files with allowed extensions
  • File Writing: Write text/binary content to files — opt-in via `--allow-write` (disabled by default)
  • Directory Validation: Check accessibility of configured directories
  • Hybrid Configuration: Command-line arguments (MCP) + config.json fallback (debugging)
  • Visual Studio 2022+ Debugging: No-argument startup support
  • Cross-Platform Path Support: Automatically handles both Windows (\) and Unix (/) path separators
  • Security: Access restricted to explicitly specified directories and file types
  • Local Development Focus: Perfect for Visual Studio 2022+ and similar environments

Installation

From PyPI (Recommended for Users)
pip install vs-filesystem-mcp-server
From Source (For Development)
  1. Ensure you have Python 3.10+ installed
  2. Clone the repository
  3. Navigate to the project directory
  4. Install dependencies using uv:
   uv sync

Quick Start

  1. For MCP usage: Add the corrected configuration to your .mcp.json
  2. For debugging: Just press F5 in Visual Studio 2022+ - uses config.json automatically
  3. Test your configuration by calling the init() tool first
  4. If init() returns errors, check your directory paths and permissions

Configuration Options

Option 1: Config.json File (Simplest - Recommended for Beginners)

The easiest way to get started! Create a config.json file:

For MCP server usage:

  • Place config.json in the same folder as your .mcp.json file (usually C:\Users\YourUsername\)

For debugging from source (Visual Studio 2022+):

  • Place config.json in the same directory as app.py (D:/Projects/filesystem_server/)
{

"allowed_dirs": [ "C:/Users/YourUsername/Documents/projects", "D:/projects", "D:/Webs" ], "allowed_extensions": [ ".py", ".js", ".ts", ".json", ".md", ".txt", ".yml", ".yaml", ".toml", ".cfg", ".ini", ".cs", ".css", ".scss", ".htm", ".html", ".xml", ".xaml" ], "allow_write": false }

Note: Set "allow_write": true to enable write_file and write_file_binary tools.

MCP Configuration (Installed via pip)

Add this to your .mcp.json file (usually C:\Users\YourUsername\ in VS 2022+):

{

"servers": { "filesystem-server": { "command": "vs-filesystem-mcp-server" } } }

Note: When installed via pip, the command is just vs-filesystem-mcp-server - no path to app.py needed!

MCP Configuration (Running from Source)

If you're developing and running from source code:

{

"servers": { "filesystem-server": { "command": "python", "args": [ "/absolute/path/to/your/project/filesystem_server/app.py" ], "cwd": "/absolute/path/to/your/project/filesystem_server" } } }

Benefits:

  • ✅ No command-line arguments needed
  • ✅ Perfect for Visual Studio 2022 debugging (just press F5)
  • ✅ Works with MCP clients when placed in correct location
  • ✅ Easy to edit and modify
  • ✅ Great for testing and development

Usage:

# For debugging in Visual Studio 2022:

python app.py # Uses config.json from same directory as app.py

For MCP server usage:

The MCP client automatically finds config.json in the .mcp.json directory

Important Location Notes:

  • 🔧 Debugging: config.json goes next to app.py
  • 🌐 MCP Server: config.json goes next to .mcp.json
  • 📁 Different locations for different use cases!
Option 2: Command-Line Arguments (Advanced - For MCP Clients)

Best for production MCP client configurations where you want everything in one place:

When Installed via pip
{

"servers": { "filesystem-server": { "command": "vs-filesystem-mcp-server", "args": [ "--allowed-dirs", "D:/projects", "D:/Webs", "--allowed-extensions", ".py", ".js", ".ts", ".json", ".md", ".txt" ] } } }

When Running from Source
python app.py --allowed-dirs "D:/projects" "D:/Webs" --allowed-extensions ".py" ".js" ".md"

With write access enabled:

python app.py --allowed-dirs "D:/projects" "D:/Webs" --allowed-extensions ".py" ".js" ".md" --allow-write true

MCP Client Configuration (.mcp.json):

{

"servers": { "filesystem-server": { "command": "python", "args": [ "/absolute/path/to/your/project/filesystem_server/app.py", "--allowed-dirs", "D:/projects", "D:/Webs", "--allowed-extensions", ".py", ".js", ".ts", ".json", ".md", ".txt" ], "cwd": "/absolute/path/to/your/project/filesystem_server" } } }

Benefits:

  • ✅ Self-contained configuration
  • ✅ No external config files needed
  • ✅ Version control friendly
  • ✅ Explicit and visible in MCP setup
Option 3: Hybrid Approach (Best of Both Worlds)

The server automatically uses command-line arguments first, then falls back to config.json if no arguments provided.

How it works:

  • MCP clients: Use command-line arguments (Option 2)
  • Visual Studio debugging: Automatically uses config.json (Option 1)
  • Priority: Command-line args override config.json when present

Benefits:

  • ✅ Works for both MCP clients and debugging
  • ✅ No conflicts between different usage scenarios
  • ✅ Flexible and developer-friendly
  • ✅ Choose the best option for each situation

Usage

Command Line Examples
# With command line arguments (MCP clients):

python app.py --allowed-dirs "D:/projects" "D:/Webs" --allowed-extensions ".py" ".js" ".md"

Using config.json fallback (Visual Studio 2022+ debugging):

python app.py

Show MCP configuration help:

python app.py --help-mcp

Available Tools
  1. init(directory, file_path) - Validates accessibility of configured directories and can optionally list a directory and/or read a file
  • directory (optional): Directory path to list contents (can be None)
  • file_path (optional): File path to read content (can be None)
  • Returns { "message": "OK", "isError": false, ... } if all directories accessible
  • Returns error details if any directories are inaccessible
  • Shows configuration source (command-line args vs config file)
  • Use this to verify your configuration before using other tools
  1. list_directory(directory, report_progress=True, batch_size=100) - Lists files and subdirectories in a given directory, with optional progress reporting
  • directory: The absolute or relative path to the directory (supports both / and \\ separators)
  • report_progress (optional): If True, returns progress information and batch details (default: True)
  • batch_size (optional): Number of items to process before reporting progress (default: 100)
  • Returns a list of file and directory names if report_progress is False
  • Returns a dictionary with contents, progress_info, total_items, and processing_time if report_progress is True
  • If an error occurs, returns a dictionary with "error" and "error_message" keys
  • No exceptions are raised - all errors are returned as part of the result
  1. read_file(file_path) - Reads the content of a specified file as text
  • Returns the file content as a string (for text files only)
  • Not suitable for binary files (images, audio, etc.)
  1. read_file_binary(file_path) - Reads the content of a specified file as base64-encoded binary
  • Returns { "content_base64": , "encoding": "base64", "error": False } on success
  • Returns an error dict if the file is not allowed or not found
  • Suitable for images, audio, and other binary files
  1. list_resources(directory=None, report_progress=True, batch_size=100) - Lists all resources (files and directories) in a directory (or all allowed directories) in MCP resource format
  • directory (optional): Directory to start from (defaults to all allowed_dirs)
  • report_progress (optional): If True, returns progress information and batches (default: True)
  • batch_size (optional): Number of resources per progress batch (default: 100)
  • Returns a list of resource objects if report_progress is False
  • Returns a dictionary with contents, progress_info, total_items, and processing_time if report_progress is True
  • Example resource object: json { "id": "D:/projects/example.txt", "type": "file", "name": "example.txt", "path": "D:/projects/example.txt", "metadata": { "size": 1234, "modified": "2025-08-18T12:34:56Z" }, "actions": ["read", "read_binary", "write", "write_binary"] }
  1. get_resource(path) - Gets metadata and actions for a specific file or directory
  • path: Absolute or relative path to the resource
  • Returns a resource object (id, type, name, path, metadata, actions) or an error dict
  • For files, includes size and modified time; for directories, includes type and actions
  • Does not return file content
  1. write_file(file_path, content) - Writes text content to a specified file (requires `--allow-write`)
  • file_path: Path to write to (must be within allowed dirs)
  • content: Text string to write
  • Raises ValueError if write access is disabled, path not allowed, extension not allowed, or IO error
  • Overwrites existing file
  • Disabled by default — enable with --allow-write flag or "allow_write": true in config.json
  1. write_file_binary(file_path, content_base64) - Writes binary content from base64 to file (requires `--allow-write`)
  • file_path: Path to write to (must be w

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