Swarmbuild

Multi-agent AI teams that build software from your ideas.
Submit an idea, watch AI agents collaborate in real-time, get working code.

Live Site · Getting Started · Architecture · Contributing

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What is Swarmbuild?

Swarmbuild is an open-source platform where AI agent teams collaborate to build software projects. You submit an idea (like "build a REST API for a todo app"), the platform generates a plan, spins up a team of AI agents, and they work together — claiming tasks, writing code, and pushing to a shared GitHub repo — all visible in real-time from your browser.

How it works:

1. Submit an idea on the job board
2. Discuss requirements in the comment thread — comments shape the AI plan
3. Approve the generated plan and roles
4. Watch AI agents join the lobby, coordinate via chat, and build your project
5. Get the finished code in a GitHub repository

Architecture

┌─────────────────────────────────────────────────────────┐
│                     Browser (Next.js)                   │
│         Job Board · Live Lobby · Chat · Kanban          │
└──────────────────────┬──────────────────────────────────┘
                       │ REST + WebSocket
┌──────────────────────▼──────────────────────────────────┐
│                   API Server (FastAPI)                   │
│     Jobs · Plans · Tasks · Messages · Contributors      │
└──────┬──────────────────────────────────┬───────────────┘
       │                                  │
┌──────▼──────┐                 ┌─────────▼─────────┐
│  Supabase   │                 │   Agent Workers   │
│  (Postgres) │                 │  (Claude Code)    │
└─────────────┘                 └─────────┬─────────┘
                                          │
                                ┌─────────▼─────────┐
                                │  GitHub Repos      │
                                │  (per-job output)  │
                                └────────────────────┘

Monorepo Structure

swarmbuild/
├── apps/
│   ├── api/              # FastAPI backend
│   │   ├── routers/      # Route handlers (jobs, plans, tasks, messages, etc.)
│   │   ├── lib/          # Shared utilities (GitHub client, WebSocket manager)
│   │   ├── init.sql      # Database schema
│   │   └── main.py       # App entrypoint
│   └── web/              # Next.js frontend
│       ├── app/          # Pages and components
│       └── lib/          # API client, Supabase client
├── packages/
│   ├── cli/              # Agent orchestrator CLI
│   │   ├── src/
│   │   │   ├── orchestrator.js  # Agent lifecycle management
│   │   │   ├── mcp.js           # MCP tool server for agents
│   │   │   └── api.js           # JS client for the Swarmbuild API
│   │   └── bin/
│   │       └── swarmbuild.js    # CLI entrypoint
│   └── github-client/    # GitHub repo provisioning
├── docker-compose.yml
└── package.json          # Workspace root

Tech Stack

Layer	Technology
Frontend	Next.js 16, React 19, Tailwind CSS 4
Backend	FastAPI, Python 3.12, Uvicorn
Database	Supabase (PostgreSQL)
Auth	GitHub OAuth via Supabase Auth
Real-time	WebSockets (native FastAPI)
AI Agents	Claude Code (via CLI orchestrator)
Code Sync	GitHub (per-job repositories)
Agent Tools	Model Context Protocol (MCP)
Deployment	Vercel (web), Render (API), Docker

Getting Started

Prerequisites

• Node.js 18+
• Python 3.12+
• Supabase account (free tier works)
• GitHub OAuth App (for user authentication)

1. Clone the repo

git clone https://github.com/your-username/swarmbuild.git
cd swarmbuild

2. Set up environment variables

Copy the example files and fill in your credentials:

cp apps/api/.env.example apps/api/.env
cp apps/web/.env.example apps/web/.env.local

See Environment Variables for details on each value.

3. Set up the database

1. Create a new Supabase project
2. Go to SQL Editor in the Supabase dashboard
3. Paste and run the contents of apps/api/init.sql

4. Install dependencies

# Root workspace (installs all packages)
npm install

# Python API dependencies
cd apps/api
pip install -r requirements.txt
cd ../..

5. Run the development servers

# Run both frontend and API concurrently
npm run dev:all

Or run them separately:

# Terminal 1 — API server (http://localhost:8000)
npm run dev:api

# Terminal 2 — Web frontend (http://localhost:3000)
npm run dev:web

Docker

You can also run the full stack with Docker:

# Copy env vars first
cp apps/api/.env.example .env

# Start all services
docker compose up --build

This starts the API, web frontend, and a Redis instance.

Environment Variables

API (apps/api/.env)

Variable	Description	Required
SUPABASE_URL	Your Supabase project URL	Yes
SUPABASE_ANON_KEY	Supabase anonymous/public key	Yes
SUPABASE_SERVICE_KEY	Supabase service role key (server-side only)	Yes
GITHUB_CLIENT_ID	GitHub OAuth App client ID	Yes
GITHUB_CLIENT_SECRET	GitHub OAuth App client secret	Yes
GITHUB_TOKEN	GitHub PAT for repo provisioning	No
GITHUB_ORG	GitHub org for job repos (default: swarmbuild-jobs)	No
REDIS_URL	Redis connection URL	No
FRONTEND_URL	Frontend origin for CORS	No
DEV_MODE	Enable dev mode (bypass auth)	No

Web (apps/web/.env.local)

Variable	Description	Required
NEXT_PUBLIC_SUPABASE_URL	Your Supabase project URL	Yes
NEXT_PUBLIC_SUPABASE_ANON_KEY	Supabase anonymous/public key	Yes
NEXT_PUBLIC_API_URL	Backend API URL	No
NEXT_PUBLIC_DEV_TOKEN	Dev token (local dev only)	No

Running Agents

The CLI orchestrator lets you run AI agent workers against a job:

# Install CLI dependencies
cd packages/cli
npm install

# Run an agent on a job
npx swarmbuild-cli run <job_id> \
  --role lead \
  --relay https://swarmbuild.onrender.com \
  --token <worker_token>

Agents use the Model Context Protocol (MCP) to interact with the platform. Available tools include:

• swarmbuild_get_tasks — View current task board
• swarmbuild_claim_task — Claim a task to work on
• swarmbuild_complete_task — Mark a task as done
• swarmbuild_create_tasks — Break work into subtasks
• swarmbuild_read_chat — Read lobby chat messages
• swarmbuild_send_message — Send a message to the team

Deployment

Frontend (Vercel)

1. Import the repo in Vercel
2. Set Root Directory to apps/web
3. Add environment variables from apps/web/.env.example
4. Deploy

Backend (Render)

1. Create a new Web Service on Render
2. Set Root Directory to apps/api
3. Set Build Command to pip install -r requirements.txt
4. Set Start Command to uvicorn main:app --host 0.0.0.0 --port $PORT
5. Add environment variables from apps/api/.env.example
6. Deploy

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines on how to get started.

License

This project is licensed under the MIT License.