Alpha version out now!

SwarmWright — Self-hosted multi-agent AI orchestration

containerized · topology-enforced · fully auditable

pull docker pull ralphbarendse/swarmwright:latest
run docker compose up
— why we built this

Most AI agent tools
pull you to one extreme.

Either you hand over full control and hope for the best, or you hand-code every step yourself. We built SwarmWright for the space in between — structured enough to trust, flexible enough to actually use.

← give away control
SwarmWright lives here
hand-roll everything →
not this
The autonomy trap

Full Autonomy

OpenAI Swarm · CrewAI · AutoGPT

Give agents a goal and let them figure out the rest. They call anything, spawn sub-agents, take actions you never explicitly authorized. Looks impressive in demos. It's a liability in production.

  • Agents call anything — no enforcement
  • You can't explain what happened
  • Important calls happen without review
  • Your compliance team will never sign off
this

Structured Agent Work

SwarmWright

Agents operate inside a topology you design. Every connection is declared upfront. Every decision leaves a reason. You approve the ones that matter. Non-technical people can read the configuration and know exactly what the system does.

  • All connections declared — nothing unchecked
  • Every edge has a stated purpose
  • Human gates built directly into workflows
  • Readable by business, ops, and compliance
not this
The rigidity trap

Custom Pipelines

LangChain scripts · DIY · hard-coded chains

Write every step by hand. It works — until it doesn't. Changing one thing breaks three others. Six months in, nobody understands it. Every new workflow is another one-off only one person can maintain.

  • Every swarm is a unique implementation
  • No standard structure to onboard into
  • Expensive to change, brittle to extend
  • Auditing means reading source code
"

SwarmWright is the operating system for your AI workforce. Structured enough to deploy with confidence. Expressive enough to handle real-world complexity. And every single decision is traceable back to the rule that caused it.

— what you get

Features

SwarmWright is opinionated by design. Every architectural choice has a reason. Every agent connection must be declared. Every action leaves a trace.

Up and running in one command.

No server to configure, no infrastructure to manage. Pull the container, point it at your API key, and your swarm is live in under a minute. Everything your agents produce is saved locally — your data never leaves your machine.

  • Works on any machine that runs Docker
  • All data stored locally in a single folder you own
  • Survives restarts — pick up exactly where you left off
  • Your LLM credentials are encrypted and never leave the container
Claude (Anthropic)
GPT-4 (OpenAI)
Runs on Docker
No cloud lock-in
Local-first data
localhost:5001
SwarmWright up and running screenshot

Know exactly what your agents can do.

Every connection between agents is declared upfront — no surprises, no agents calling things they shouldn't. If an agent tries to do something it wasn't given permission to do, it's stopped and flagged immediately. You stay in control.

  • Define which agents can talk to which — visually
  • Each connection has a stated reason, written in plain language
  • Unauthorized actions are caught and surfaced, not silently skipped
  • Your compliance team can read the rules — no code required

Design your AI team visually.

Drag agents onto a canvas, draw connections between them, and describe why each connection exists. It looks and feels like sketching on paper — because it should. No YAML to write by hand. No diagram that's out of date the moment you deploy.

  • Drag-and-drop canvas — place agents, draw connections
  • The diagram is the configuration — always in sync
  • Each connection asks: what is this for? Forces clear thinking
  • Color-coded by role so the structure is obvious at a glance
Swarm canvas screenshot

Roles your team already understands.

SwarmWright organizes agents the same way good teams are organized — strategy at the top, execution at the bottom, coordination in the middle. Everyone knows who's responsible for what.

  • Policy — sets the rules and goals
  • Orchestrator — coordinates the work
  • Executioner — gets things done
  • Perceptionist — reads and interprets data

Write what your agents believe in.

Each agent has a constitution — a plain-language document that describes its role, values, and what it knows. Your Finance manager can read it. Your compliance officer can sign off on it. No prompt engineering required.

  • Written in plain English — readable by anyone
  • Built-in editor with live preview
  • Attach company knowledge and procedures directly to agents
Constitution editor screenshot

See every decision, always.

Every action an agent takes is recorded with a human-readable reason. No black boxes. You can trace any outcome back to the exact decision that caused it — useful for compliance, debugging, and just knowing what happened.

  • Every step logged with a plain-language reason
  • Full history of what each agent did and why
  • Unexpected behavior flagged clearly, not buried in logs

Give your agents superpowers, safely.

Agents can run Python scripts, query databases, call external APIs, and process files — but always in a secure sandbox. A misbehaving script can't take down your whole system. You decide what tools are available and to whom.

  • Write custom tools in Python and attach them to agents
  • Each tool runs in isolation — nothing can escape the sandbox
  • Tools are reusable across the whole organization
  • Permissions are explicit — no tool runs without being declared

Stay in control when it matters.

Agents know when a decision is too important to make alone. They pause and send it to your inbox. You approve, reject, or add context — and the work continues from exactly where it stopped. You're never out of the loop.

  • Agents ask before acting on high-stakes decisions
  • Inbox for approvals with full context attached
  • Work resumes from the exact point it paused
Human in the loop inbox screenshot

Use the AI model you trust.

Bring your own Anthropic or OpenAI key. Switch providers without rebuilding anything. Your credentials are encrypted and stored locally — never sent to a third party. Different swarms can run on different models.

  • Works with Claude (Anthropic) and GPT-4 (OpenAI)
  • Switch models from the Settings screen — no code changes
  • API keys encrypted and stored locally

Share knowledge across your whole team.

Upload documents, procedures, and reference material once — and make them available to any agent that needs them. Company-wide policies, department rules, or workflow-specific context: everything is organized and stays up to date.

  • Company-wide documents available to all agents
  • Department-level rules scoped to the right teams
  • Workflow-specific context kept private to one swarm

Watch your swarm work in real time.

A live dashboard shows every agent action as it happens. See which agent is working, what it's doing, and how long it's taking. Catch problems the moment they appear — not hours later when someone notices something went wrong.

  • Live feed of every agent action as it happens
  • Full history of every past run, searchable and filterable
  • Problems are flagged immediately with context

One command.
Your swarm runs.

no broker setup · no cluster · no build step

docker pull ralphbarendse/swarmwright:latest