🎻 Mozart

Mozart is the local conductor for AI agents. Gateways execute. Mozart decides.

What problem does Mozart solve?

You have Ollama, OpenRouter, LiteLLM, OpenCode, OpenClaw... multiple gateways, multiple models. Every time you ask your agent to do something, you have to guess which model to use. Cheap one for simple stuff? Premium for complex? Local for sensitive files?

Mozart decides for you. It detects every gateway and model you already have, classifies your task, scans for secrets, estimates cost, and routes to the best model — automatically.

Before Mozart:  "Hmm, should I use GPT-4 or Llama for this? Is there a secret in this file?"
After Mozart:   "Just ask. Mozart handles it."

⚡ Quick Install

npm install -g mozart-router
mozart-router doctor

That's it. Mozart finds everything you already have configured.

🎯 What Mozart does

🚀 30-Second Demo

# See what's on your machine
mozart-router doctor

# Simulate routing for a task
mozart-router simulate "debug my Next.js build error"

# Route a real task
mozart-router route "write Playwright tests for the login page"

# Understand the decision
mozart-router why

# Session report
mozart-router report

# See the dashboard
mozart-router start --port=4444
# Open http://localhost:4444

🔌 Integration modes

Mozart works however you need it to:

# As a CLI tool
mozart-router doctor

# As an SDK in your agent code
import { Mozart } from 'mozart-router'

# As a skill for OpenCode / OpenClaw / Hermes
mozart-router init --gateway opencode

# As an MCP server (Claude Desktop, Cursor, Continue.dev)
mozart-router mcp

# As an OpenAI-compatible proxy
mozart-router proxy --port=4445

# As a streaming middleware (SSE)
mozart-router stream --port=4445

📦 Supported Gateways

🧭 How routing works

Your task → "debug the authentication error"
                ↓
         Task Classifier → debugging, high complexity, very_high context
                ↓
         Privacy Guard  → scans for secrets, API keys
                ↓
         Policy Engine  → your budget, privacy preferences
                ↓
         Routing Engine → scores all available models on 7 dimensions
                ↓
         Output         → "qwen3:8b via OpenClaw (score 0.92, cost $0)"
                           + fallback chain
                           + full explanation

📊 Commands

📚 Docs