# Hostname MCP Server
A lightweight Model Context Protocol (MCP) server focused on hostname detection with system information. Perfect for AI assistants to automatically identify which machine they're working with.
Generated by Claude Sonnet 4, directed by leependu.
## Features
š **Secure**: Only reads system information, never executes arbitrary commands
š·ļø **Focused**: Hostname detection first, system specs second
ā” **Lightweight**: Minimal dependencies and fast startup
šÆ **Purpose-built**: Designed specifically for Claude Desktop workflow optimization
## Tools Provided
### `get_hostname`
Returns just the system hostname - perfect for quick machine identification.
### `get_system_info`
Comprehensive system information including:
- Hostname and platform details
- CPU count and memory information
- OS version and architecture
- System uptime
- User information
## Installation
1. Install dependencies:
```bash
npm install
```
2. Build the TypeScript:
```bash
npm run build
```
3. Test the server:
```bash
npm start
```
## Usage with Claude Desktop
Add to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"hostname": {
"command": "node",
"args": [
"/path/to/hostname-mcp/build/index.js"
]
}
}
}
```
## Development
- `npm run build` - Build TypeScript to JavaScript
- `npm run dev` - Watch mode for development
- `npm start` - Run the built server
## Security
This server is designed to be secure by default:
- Only reads system information using Node.js `os` module
- No arbitrary command execution
- No environment variable exposure
- No sensitive data access
## Version 2.0 Changes
- **Removed `get_environment_context`**: Eliminated potential security risk of exposing environment variables
- **Removed `get_quick_summary`**: Redundant information already available in other tools
- **Focused approach**: Now provides just hostname and system info - clean and secure
## Project Context
Created as part of a workflow optimization to automatically identify which machine Claude is working with, eliminating the need to manually specify the computer at the start of each conversation.
Perfect for users with multiple development machines who want streamlined AI assistance.
