Multi-agent orchestration for Claude Code, Codex, Gemini CLI, and other AI coding assistants.
_{Built by desplega.sh — by builders, for builders.}

agent-swarm.mp4

_{▸ daily evolution · slack → pr · Making of}

What if your AI agents remembered everything, learned from every mistake, and got better with every task?

What it does

Agent Swarm runs a team of AI coding agents that coordinate autonomously. A lead agent receives tasks — from Slack, GitHub, GitLab, email, or the API — breaks them down, and delegates to worker agents running in Docker containers. Workers execute tasks, ship code, and write their learnings back to a shared memory so the whole swarm gets smarter every session.

Learn more in the architecture overview.

flowchart LR
    subgraph IN["Tasks come in"]
        direction TB
        S["Slack"]
        G["GitHub / GitLab"]
        E["Email"]
        A["API / CLI"]
    end

    LEAD(["Lead Agent<br/>plans &amp; delegates"])

    subgraph WORKERS["Workers in Docker"]
        direction TB
        W1["Worker"]
        W2["Worker"]
        W3["Worker"]
    end

    subgraph BRAIN["Persistent brain"]
        direction TB
        MEM["Memory<br/>(vector search)"]
        ID["Identity<br/>(SOUL, CLAUDE.md)"]
    end

    subgraph OUT["Work ships"]
        direction TB
        PR["Pull Requests"]
        REPLY["Slack replies"]
        EMAIL["Email replies"]
    end

    IN --> LEAD --> WORKERS
    WORKERS -->|reads context| BRAIN
    WORKERS -->|writes learnings| BRAIN
    WORKERS --> OUT

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Highlights

• Lead/worker orchestration in Docker — isolated dev environments, priority queues, pause/resume across deploys. Architecture →
• Compounding memory & persistent identity — agents remember past sessions and evolve their own persona, expertise, and notes. Memory → · Agents →
• Multi-channel inputs — Slack, GitHub, GitLab, email, Linear, and the HTTP API all create tasks. Integrations
• Workflow engine with Human-in-the-Loop — DAG-based automation with approval gates, retries, and structured I/O. Workflows →
• Scheduled & recurring tasks — cron-based automation for standing work. Scheduling →
• Multi-provider — run with Claude Code, OpenAI Codex, or pi-mono. Harness config → · Add a new provider →
• Skills & MCP servers — reusable procedural knowledge and per-agent MCP servers with scope cascade. MCP tools →
• Real-time dashboard — monitor agents, tasks, and inter-agent chat. app.agent-swarm.dev →

Quick Start

Prerequisites: Docker and a Claude Code OAuth token (claude setup-token).

The fastest way is the onboarding wizard — it collects credentials, picks presets, and generates a working docker-compose.yml:

bunx @desplega.ai/agent-swarm onboard

Prefer manual setup? Clone and run with Docker Compose:

git clone https://github.com/desplega-ai/agent-swarm.git
cd agent-swarm
cp .env.docker.example .env
# edit .env — set API_KEY and CLAUDE_CODE_OAUTH_TOKEN
docker compose -f docker-compose.example.yml --env-file .env up -d

The API runs on port 3013, with interactive docs at http://localhost:3013/docs and an OpenAPI 3.1 spec at http://localhost:3013/openapi.json.

Other setups

• Local API + Docker workers — run the API on your host, workers in Docker. See Getting Started.
• Claude Code as the lead agent — bunx @desplega.ai/agent-swarm connect, then tell Claude Code to register as the lead.

How It Works

You (Slack / GitHub / Email / CLI)
        |
   Lead Agent  ←→  MCP API Server  ←→  SQLite DB
        |
   ┌────┼────┐
Worker  Worker  Worker
(Docker containers with full dev environments)

1. A task arrives via Slack DM, GitHub @mention, email, or the API.
2. The lead plans and delegates subtasks to workers.
3. Workers execute in isolated Docker containers (git, Node.js, Python, etc.).
4. Progress streams to the dashboard, Slack threads, or the API.
5. Results ship back out as PRs, issue replies, or Slack messages.
6. Session learnings are extracted and become memory for future tasks.

More detail in the task lifecycle docs.

Integrations

Integration	What it does	Setup
Slack	DM or @mention the bot to create tasks; workers reply in threads	Guide
GitHub App	@mention or assign the bot on issues/PRs; CI failures create follow-up tasks	Guide
GitLab	Same model as GitHub — webhooks on issues/MRs, glab preinstalled in workers	Guide
AgentMail	Give each agent an inbox; emails become tasks or lead messages	Guide
Linear	Bidirectional ticket sync via OAuth + webhooks	Guide
Sentry	Workers can triage Sentry issues with the /investigate-sentry-issue command	Guide

Dashboard

Real-time monitoring of agents, tasks, and inter-agent chat. Use the hosted version at app.agent-swarm.dev, or run locally:

cd new-ui && pnpm install && pnpm run dev

Opens at http://localhost:5274.

CLI

bunx @desplega.ai/agent-swarm <command>

Command	Description
onboard	Set up a new swarm from scratch (Docker Compose wizard)
connect	Connect this project to an existing swarm
api	Start the API + MCP HTTP server
worker	Run a worker agent
lead	Run a lead agent
docs	Open documentation (--open to launch in browser)

Deployment

For production deployments (Docker Compose with multiple workers, systemd for the API, graceful shutdown, integration config), see DEPLOYMENT.md and the deployment guide.

Documentation

Everything lives at docs.agent-swarm.dev. Good starting points:

• Getting Started — install, configure, and run your first task
• Architecture overview — how the swarm is wired together
• CLI reference and Environment variables
• API reference — every HTTP endpoint

Contributing

We love contributions! Whether it's bug reports, feature requests, docs improvements, or code — all are welcome.

See CONTRIBUTING.md to get started. The quickest way to contribute:

1. Fork the repo
2. Create a branch (git checkout -b my-feature)
3. Make your changes
4. Open a PR

Join our Discord if you have questions or want to discuss ideas.

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License

MIT — 2025-2026 desplega.sh