---
title: "Deploy harnessrouter"
description: "Unified interface for agent harnesses."
category: "AI/ML"
url: https://railway.com/deploy/harnessrouter-1
---

# Deploy harnessrouter

Unified interface for agent harnesses.

**[Deploy harnessrouter on Railway](https://railway.com/template/harnessrouter-1)**

Machine-readable deploy manifest (JSON, validated by TemplateCI): https://railway.com/deploy/harnessrouter-1/manifest.json

- **Creator:** kmaki's Projects
- **Category:** AI/ML

## Template content

### app

- **Image:** harnessrouter/harnessrouter:0.20.1
- **Public domain:** Yes

## Documentation

# Deploy and Host HarnessRouter on Railway

HarnessRouter is a self-hosted AI agent workspace that unifies a browser console, gateway, and runner in one Docker image. It supports multiple agent harnesses, streaming sessions, files, workspaces, and provider integrations while keeping credentials and durable state under your Railway project. A persistent volume preserves the local SQLite data and installed tools.

[![Deploy on Railway](https://railway.com/button.svg)](https://railway.com/deploy/z1hHX4)

## About Hosting HarnessRouter on Railway

Railway runs the published Docker Hub image as one HTTP service. The console is exposed publicly on port 3000, while the gateway and runner remain loopback-only inside the container. A Railway volume mounted at `/data` preserves application state across redeployments.

## Tech Stack

- HarnessRouter Community Edition
- Next.js and React web console
- Python FastAPI gateway and runner
- SQLite local persistence
- Docker Hub image `harnessrouter/harnessrouter:0.20.1`
- Railway service domain and persistent volume

## Why Deploy HarnessRouter on Railway

Railway provides a fast one-click path to a managed Docker deployment with TLS, public routing, logs, restarts, and persistent storage. The single-service design keeps the console, gateway, and runner together, so there are no extra databases or internal services to configure for the self-hosted edition.

## Common Use Cases

- Run AI coding agents from a browser-based console
- Connect Claude, OpenAI, Gemini, and other provider integrations
- Maintain durable agent workspaces and session files
- Expose the HarnessRouter API to internal products
- Experiment with multiple harness backends in one private deployment

## Deployment Notes

- Railway routes the HTTP service through `PORT=3000`; the image listens on `0.0.0.0:3000`.
- `HR_AUTH_USER` defaults to `harnessrouter` and is exposed explicitly for the initial console login.
- `HR_AUTH_PASSWORD` is generated with a Railway secret expression. Change the password from the profile page after first login if desired.
- `HR_DATA_DIR=/data` matches the persistent Railway volume mount. The first boot installs enabled agent CLIs into this volume and may take several minutes.
- Add provider credentials through the HarnessRouter console after deployment. No provider API key is bundled in the template.
- The Docker image has its own entrypoint and does not need a Railway `startCommand` override.

## Dependencies for HarnessRouter on Railway

HarnessRouter is self-contained. It requires one Docker service, one public HTTP domain, and one persistent volume for its SQLite databases, files, workspaces, credentials, and first-run agent installations.

### Deployment Dependencies

| Service | Image | Port | Volume |
|---------|-------|------|--------|
| app | harnessrouter/harnessrouter:0.20.1 | 3000 | /data |

### Template Variables

| Variable | Default |
|----------|---------|
| `PORT` | `3000` |
| `HR_DATA_DIR` | `/data` |
| `HR_AUTH_USER` | `harnessrouter` |
| `HR_AUTH_PASSWORD` | `${{secret(32, "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789")}}` |

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