Omnara transforms your AI agents (Claude Code, Cursor, GitHub Copilot, and more) from silent workers into communicative teammates. Get real-time visibility into what your agents are doing, respond to their questions instantly, and guide them to success - all from your phone.

✨ Key Features

Feature	Description
📊 Real-Time Monitoring	See every step your AI agents take as they work
💬 Interactive Q&A	Respond instantly when agents need guidance
📱 Mobile-First Design	Full control from your phone, tablet, or desktop
🔔 Smart Notifications	Get alerted only when your input is needed
🎯 Universal Dashboard	All your AI agents in one unified interface

🎬 See It In Action

The moment your agent needs help, you're there. No more returning to failed jobs hours later.

💡 Why Omnara?

We built Omnara because we were tired of:

❌ Starting long agent jobs and finding them stuck hours later
❌ Missing critical questions that blocked progress
❌ Having no visibility into what our AI was actually doing
❌ Being tied to our desks while agents worked

Now you can:

✅ Launch agents and monitor them from anywhere
✅ Get push notifications when input is needed
✅ Send real-time feedback to guide your agents
✅ Have confidence your AI workforce is productive

🏗️ Architecture Overview

Omnara uses the Model Context Protocol (MCP) to enable seamless communication between your agents and the dashboard.

graph TB
    subgraph "Your AI Agents"
        A[🤖 AI Agents<br/>Claude, Cursor, Copilot]
    end

    subgraph "Omnara Platform"
        S[🔄 MCP Server]
        DB[(📊 Database)]
        API[🌐 API Server]
    end

    subgraph "Your Devices"
        M[📱 Mobile App]
        W[💻 Web Dashboard]
    end

    A -->|Log activities| S
    S -->|Store data| DB
    DB -->|Real-time sync| API
    API -->|Push updates| M
    API -->|Push updates| W
    M -->|Send feedback| API
    W -->|Send feedback| API
    API -->|Store feedback| DB
    S <-->|Agent queries| DB

    style A fill:#e3f2fd,stroke:#1976d2,stroke-width:3px
    style S fill:#c8e6c9,stroke:#388e3c,stroke-width:2px
    style DB fill:#ffccbc,stroke:#d84315,stroke-width:2px
    style API fill:#c8e6c9,stroke:#388e3c,stroke-width:2px
    style M fill:#f8bbd0,stroke:#c2185b,stroke-width:3px
    style W fill:#f8bbd0,stroke:#c2185b,stroke-width:3px

🔧 Technical Stack

Backend: FastAPI with separate read/write servers for optimal performance
Frontend: React (Web) + React Native (Mobile)
Protocol: Model Context Protocol (MCP) + REST API
Database: PostgreSQL with SQLAlchemy ORM
Auth: Dual JWT system (Supabase for users, custom for agents)

🚀 Quick Start

For Claude Code Users

Download the app or visit omnara.ai
Launch the webhook server with the command in the onboarding flow
Create your agent with the webhook endpoint and API key
Start monitoring your AI workforce!

For Developers

🛠️ Development Setup

Prerequisites

Python 3.10+
PostgreSQL
Node.js (for CLI tools)

Setup Steps

Clone and enter the repository

git clone https://github.com/omnara-ai/omnara
cd omnara

Set up Python environment

python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
make dev-install

Generate JWT keys
```
python scripts/generate_jwt_keys.py
```

Configure environment (create .env file)

DATABASE_URL=postgresql://user:password@localhost:5432/omnara
SUPABASE_URL=https://your-project.supabase.co
SUPABASE_ANON_KEY=your-anon-key
JWT_PRIVATE_KEY='-----BEGIN RSA PRIVATE KEY-----\n...'
JWT_PUBLIC_KEY='-----BEGIN PUBLIC KEY-----\n...'

Initialize database
```
cd shared/
alembic upgrade head
cd ..
```

Run services

# Terminal 1: MCP + REST Server
python -m servers.app

# Terminal 2: Backend API
cd backend && python -m main

📚 Integration Guide

Method 1: MCP Configuration

{
  "mcpServers": {
    "omnara": {
      "url": "https://api.omnara.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Method 2: Python SDK

from omnara import OmnaraClient
import uuid

client = OmnaraClient(api_key="your-api-key")
instance_id = str(uuid.uuid4())

# Log progress and check for user feedback
response = client.log_step(
    agent_type="claude-code",
    step_description="Analyzing codebase structure",
    agent_instance_id=instance_id
)

# Ask for user input when needed
answer = client.ask_question(
    question="Should I refactor this legacy module?",
    agent_instance_id=instance_id
)

Method 3: REST API

curl -X POST https://api.omnara.ai/api/v1/steps \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"step_description": "Starting deployment process"}'

🤝 Contributing

We love contributions! Check out our Contributing Guide to get started.

Development Commands

make lint       # Run code quality checks
make format     # Auto-format code
make test       # Run test suite
make dev-serve  # Start development servers

📊 Pricing

Plan	Price	Features
Free	$0/mo	20 agents/month, Core features
Pro	$9/mo	Unlimited agents, Priority support
Enterprise	Contact Us	Teams, SSO, Custom integrations

🆘 Support

📜 License

Omnara is open source software licensed under the Apache 2.0 License.

Built with ❤️ by the Omnara team

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