Use Smack as a native macOS messaging interface for AI agents

Problem

Interacting with AI agents and development tools typically means opening a browser tab, navigating to a web UI, or switching to a terminal window. Each context switch pulls you out of your workflow. Browser-based chat interfaces are heavy -- they consume memory, compete for tab space, and lack native OS integration like keyboard shortcuts and notifications. Terminal-based interfaces are fast but limited in formatting and lack persistent conversation history with a clean UI. There is no lightweight, always-available messaging layer purpose-built for developer-to-AI communication on macOS.

Solution

Use Smack -- a native macOS instant messaging app built in Swift -- as a dedicated interface for communicating with AI agents and tools. It connects to a server component that routes messages between the client and your AI backends.

Install and launch Smack:

# Download Smack.dmg from the releases page
curl -L -o Smack.dmg \
  https://github.com/schappim/smack-server/releases/latest/download/Smack.dmg

# Mount, install, and launch
hdiutil attach Smack.dmg
cp -R /Volumes/Smack/Smack.app /Applications/
hdiutil detach /Volumes/Smack
open /Applications/Smack.app

Set up the smack-server backend:

# Clone and run the server component
git clone https://github.com/schappim/smack-server.git
cd smack-server
npm install
npm start

Configure agent routing in the server:

{
  "port": 3000,
  "agents": [
    {
      "name": "claude",
      "endpoint": "http://localhost:8080/chat",
      "description": "General coding assistant"
    },
    {
      "name": "reviewer",
      "endpoint": "http://localhost:8081/chat",
      "description": "Code review agent"
    }
  ]
}

Build a minimal agent endpoint that Smack routes to:

from flask import Flask, request, jsonify
import anthropic

app = Flask(__name__)
client = anthropic.Anthropic()

@app.route("/chat", methods=["POST"])
def chat():
    message = request.json["message"]
    response = client.messages.create(
        model="claude-opus-4-6",
        max_tokens=1024,
        messages=[{"role": "user", "content": message}],
    )
    return jsonify({"reply": response.content[0].text})

if __name__ == "__main__":
    app.run(port=8080)

The daily workflow becomes:

1. Cmd+Space -> "Smack" -> Enter       (launch via Spotlight)
2. Select agent channel (e.g., #claude)
3. Type message, get response instantly
4. Cmd+Tab back to editor

For teams, deploy smack-server centrally:

# docker-compose.yml for shared deployment
docker compose up -d smack-server

# All developers point Smack.app at the shared server
# Agents, API keys, and routing are configured once

Why It Works

A native Swift app on macOS launches instantly, uses minimal memory compared to an Electron or browser-based alternative, and integrates with the OS for notifications, keyboard shortcuts, and window management. The messaging paradigm is familiar -- it looks and feels like any chat app -- so there is no learning curve. The server component decouples the UI from the backend, meaning you can swap AI providers, add custom agents, or route to internal tools without changing the client app. Persistent conversation history means you can pick up where you left off, unlike terminal sessions that get lost when you close the window.

Context

• Smack is distributed as a .dmg -- no Homebrew, pip, or npm needed on the client side
• The server component (smack-server) is open source at github.com/schappim/smack-server and handles WebSocket connections from the native client
• You can run multiple agent channels simultaneously -- one for code review, one for general questions, one for DevOps commands
• Native macOS apps get proper Notification Center integration, so agent responses appear as system notifications when Smack is in the background
• For teams, the centralized server means agent configurations are shared and API keys stay on the server rather than on individual machines
• The same architectural pattern (native messaging shell + backend router) could be built with SwiftUI, AppKit, or Tauri for cross-platform support
• This is similar in concept to Slack but purpose-built for dev-to-AI interaction with lower overhead