@developkiko/desktop-commander

🇷🇺 Русская версия

📋 Table of Contents

• What is this?

• ✨ What's Fixed?

• 📦 Installation

• ⚙️ Configuration in Chatbox AI

• 🔧 Available Tools

• 💡 Usage Examples

• 📚 Why This Fork?

• 🔗 Links

Related MCP server: Simple SSH MCP Server

🧐 What is this?

Desktop Commander is an MCP (Model Context Protocol) server that gives AI assistants like Claude, Chatbox, Cursor, and others direct access to your computer's file system and terminal.

With it, an LLM agent can:

• 📁 Create, read, edit, and delete files and folders

• 🔍 Search for files and text across your project

• 🖥️ Run terminal commands and Python scripts

• 📄 Work with PDFs, Excel files, and images

• ✏️ Perform surgical text replacements with edit_block

This is a maintained fork with critical bug fixes — see below.

✨ What's Fixed?

The original Desktop Commander had a critical issue: no content size limits in file operations. When an AI tried to write files larger than ~500 lines, the entire content was sent as a single MCP JSON-RPC message, causing:

❌ Unterminated string in JSON at position 37769

🔴 Problem 1: write_file buffer overflow

Before (original): Writing 5000 lines → 1 giant JSON-RPC string → stdio buffer overflows → JSON.parse crash

After (fixed): Content is automatically split into 30-line chunks, each written in a separate MCP call:

🔴 Problem 2: No size validation for read/write

Before: writeFile() could receive 500MB+ in one call → OOM. readFile() could load a 2GB file → heap overflow.

After: Explicit byte limits with clear error messages:

• writeFile(): 10 MB max content size

• readFileInternal(): 50 MB max file size

• handleWriteFile(): 10,000 lines hard cap with auto-chunking up to that limit

🔴 Problem 3: Windows path handling

Paths are now properly normalized regardless of slash direction (/ vs \).

📦 Installation

Option A: Via npx (recommended)

npx @developkiko/desktop-commander@latest

Option B: Global install

npm install -g @developkiko/desktop-commander
desktop-commander

Option C: Local development

# Clone and build
git clone https://github.com/developkiko/DsktpCmndr.git
cd DsktpCmndr
npm install
npm run build

# Run directly
node dist/index.js

⚙️ Configuration in Chatbox AI

To use this server in Chatbox AI:

1. Open Settings → MCP Servers

2. Click Add MCP Server (or edit existing)

3. Fill in:

4. Save and restart Chatbox

Or, for the local build:

• Command: node

• Args: E:\LLM\mcps\DsktpCmndr\dist\index.js

🔧 Available Tools

💡 Usage Examples

📁 Creating a project structure

"Create folders for a React project: src/components, src/pages, src/hooks, public, and a blank README.md"

flowchart LR
    A["🖥️ You ask AI"] --> B["create_directory('src/components')"]
    A --> C["create_directory('src/pages')"]
    A --> D["create_directory('src/hooks')"]
    A --> E["create_directory('public')"]
    A --> F["write_file('README.md','# My Project')"]

🔍 Searching for text in files

"Find all .ts files in E:\WORK\my\GameDev that contain GameLoop and show the first 10 lines"

1. start_search(path="E:\WORK\my\GameDev", pattern="GameLoop", searchType="content", filePattern="*.ts")

2. get_more_search_results(sessionId)

3. For each result: read_file(path, offset=0, length=10)

📊 Analyzing a large CSV

Bad approach: ❌ "Read this 500MB CSV file" → MCP buffer overflow

Good approach: ✅ "Read the first 5 lines of sales.csv to see headers, then start Python and analyze with pandas"

1. read_file("sales.csv", offset=0, length=5)  → shows headers
2. start_process("python -i")
3. import pandas as pd
4. df = pd.read_csv("E:/DATA/sales.csv")       ← Python reads directly
5. df.groupby("Region")["Amount"].sum()         ← analysis in Python

🐍 Running a Python script

"Run E:\scripts\backup.py and tell me what it outputs"

1. start_process("python E:\scripts\backup.py")
2. read_process_output(pid)

✏️ Replacing text across files

"Replace console.log with logger.info in all .js files in E:\WORK\app"

1. start_search(path="E:\WORK\app", pattern="console.log", filePattern="*.js")
2. For each match: edit_block(file, old="console.log", new="logger.info")

📚 Why This Fork?

The original Desktop Commander by wonderwhy-er is a fantastic project. This fork exists to:

1. Fix the critical auto-chunking bug — large files would crash the MCP transport

2. Add proper size validation — prevent OOM from accidental giant file reads/writes

3. Provide ongoing maintenance — as an independent community fork

4. Ensure Windows compatibility — proper path handling for Windows users

All credit for the original architecture goes to wonderwhy-er and contributors.

🔗 Links