Orca Tutorial 2026: Build Multi-Agent AI Systems with TypeScript

What is Orca?

Orca is an Agent Development Environment (ADE) designed for developers who need to work with multiple AI agents simultaneously. Instead of managing individual agents one at a time, Orca lets you orchestrate a fleet of parallel agents—whether you're using Claude, local models, or custom implementations. The problem it solves: coordinating multiple AI coding agents across desktop, mobile, and remote environments without building your own infrastructure from scratch.

What is Orca?

Orca positions itself as a unified IDE for agent orchestration. You can run any coding agent using your own subscriptions (OpenAI, Anthropic, etc.), avoiding vendor lock-in. The platform provides native applications for desktop and mobile, plus support for remote runtimes, so your agents can work wherever your code lives—local machines, cloud environments, or hybrid setups.

Key Features

• Multi-agent orchestration: Manage multiple AI agents in parallel rather than sequential execution
• Cross-platform availability: Desktop, mobile, and remote runtime support with a consistent interface
• Bring your own subscription: Use your existing API keys for Claude, OpenAI, or other providers—no metered billing from Orca
• Agent IDE: Purpose-built development environment for writing, debugging, and monitoring agent behavior
• CLI tools: Command-line interface for automation and CI/CD integration
• Open-source foundation: Built on TypeScript and available on GitHub for community contribution and customization

Getting Started

Installation

Start by cloning the repository and installing dependencies:

git clone https://github.com/stablyai/orca.git
cd orca
npm install

For development mode with TypeScript compilation:

npm run dev

You can also install Orca as a CLI tool globally:

npm install -g @stablyai/orca

Initial Configuration

Create a configuration file to specify your agent fleet. Orca uses a JSON or YAML-based config:

{
  "agents": [
    {
      "name": "code-reviewer",
      "model": "claude-3-5-sonnet",
      "provider": "anthropic",
      "apiKey": "${ANTHROPIC_API_KEY}"
    },
    {
      "name": "test-generator",
      "model": "claude-3-5-sonnet",
      "provider": "anthropic",
      "apiKey": "${ANTHROPIC_API_KEY}"
    }
  ],
  "runtime": "local"
}

Export your API keys:

export ANTHROPIC_API_KEY="your-key-here"
export OPENAI_API_KEY="your-key-here"

Running Your First Agent Fleet

Launch Orca with your configuration:

orca start --config ./orca.json

The desktop or mobile application will open, showing a dashboard of your agents, their status, and real-time logs. You can send tasks to specific agents or broadcast to the entire fleet.

When to Use Orca

Parallel Code Review at Scale

Imagine you have a CI/CD pipeline where every pull request needs both functional review and security analysis. Instead of running agents sequentially (which doubles your time), Orca lets you spawn a code-reviewer agent and a security-auditor agent in parallel. Both analyze your code simultaneously and report findings, cutting review time in half while improving coverage.

Distributed Testing Infrastructure

AI-powered test generation is powerful but expensive when done serially. Teams use Orca to run multiple test-generation agents across different modules simultaneously—one for unit tests, one for integration tests, one for edge cases. Each agent works on its specialty in parallel, then their outputs are merged into a comprehensive test suite.

Multi-Model Consensus Systems

Some organizations route complex tasks through multiple AI models and aggregate their responses. With Orca, you can spin up agents using Claude for creative problem-solving, GPT-4 for structured analysis, and a local model for code completion—all working on the same task in parallel to build consensus-based solutions.

Best for: AI developers, engineering teams scaling agent usage, organizations that want flexibility in AI provider selection, and projects where parallel execution of coding tasks offers real business value.

Takeaway

Orca solves a real coordination problem for teams moving beyond single-agent workflows. If you're already comfortable with AI agents and need to orchestrate multiple ones without building custom infrastructure, it's worth evaluating. The TypeScript foundation makes it accessible to JavaScript developers, and the open-source nature means you can extend it for your specific use case. Start with the desktop app to understand the workflow, then migrate to CLI or remote runtimes as your needs scale.