The unified interface for agent harnesses.

Build agent products without handling harness engineering. HarnessRouter is the infrastructure layer that turns existing harnesses like Codex and Claude Code into plug-and-play agent backends, letting your product run tasks, retrieve results, and switch harnesses through one API.

HarnessRouter implements the Unified Harness Protocol (UHP) and provides an OpenAI Responses-compatible API, handling persistent sessions, streaming progress, files, artifacts, cancellation, and structured failures.

#Switch harnesses. Optimize cost and latency.

Eight harness × model configurations on the same task. Each metric compares its best and worst results. The lowest-cost and fastest configurations vary by task. Methodology

[!TIP] Get started: Run locally · Integrate into your product · Starter kits · Use managed Cloud

#Quickstart

Self-host Community Edition with your own provider keys, on infrastructure you control.

Start with one Docker command, wait for the first launch, then connect a model provider and run your first task.

You need: Docker · About 4 GB of disk · A provider API key

No HarnessRouter account required. No bundled model or trial key.

#1. Start HarnessRouter

docker run -d --name harnessrouter \
  -p 127.0.0.1:3000:3000 \
  -v harnessrouter:/data \
  harnessrouter/harnessrouter

Docker pulls the image if needed. The named volume preserves your database, files, installed harness CLIs, and workspaces between restarts.

Existing installation or custom setup

Already installed? docker pull harnessrouter/harnessrouter downloads the latest image but does not upgrade a running container. Follow the upgrade and backup guide.

Port 3000 busy? Use -p 127.0.0.1:3100:3000 and open port 3100 instead. Keep the loopback binding while using the initial credentials.

Do not add --user. The entrypoint and Runner need root to manage per-session users. The Console and Gateway run unprivileged; agent processes run as their session’s user.

For version pinning, Compose, and scripted setup, see the setup guide.

#2. Wait for the first launch

docker logs -f harnessrouter

The first launch installs the enabled harness CLIs. Continue when the logs show:

[harnessrouter] ready on :3000

Press Ctrl+C to stop following logs. The container keeps running.

Console not ready or a harness missing?

If the browser refuses the connection, retry after a few seconds while the Console finishes starting. For a missing harness, check backends available: and any requested but not installed warning in the logs.

#3. Open the console

Open http://localhost:3000, or your chosen host port, and sign in:

[!WARNING] Change the default password in Profile. Keep the instance local until you change it. Saving briefly restarts the Console and signs out other browsers.

See the sign-in screen

Using an existing volume or custom credentials? Check credential precedence and setup.

These credentials sign you into the Console. You do not need a HarnessRouter API key to run tasks here.

#4. Connect a model provider

Open Bring Your Own Key in the sidebar and press Add Integration. Choose a provider, give the integration a name, and add its API key. Its supported models become available in the Console.

This provider key authorizes model requests. It is separate from the HarnessRouter API key used for product integration below.

See the provider setup screen

#5. Run your first task

Open Agent harnesses, choose a supported harness, and select New task. Pick an available model and give the agent a concrete task. Follow live progress and open the files it produces in the same session.

_{In the illustrative run above, Hermes reviews a fictional NDA and produces a redlined version, a clean copy, and a negotiation memo.}

#Configure a custom harness (optional)

Built-in harnesses work without this step. Create a custom harness when you want reusable behavior tailored to your product.

1. Create. Select New harness in Agent harnesses. In Add harness, set the Name, Base harness, and Default model together, then select Create and configure.
2. Customize. In Harness Settings, add Agent instructions, configure Tools (use Add MCP for an optional MCP server), and add Skills as needed.
3. Save and test. Select Save Changes, then Run Task to test the saved configuration.

You can change the default model later in Settings, but the base harness cannot be changed after creation.

Watch the configuration walkthrough · 48 seconds

_{Configure DeepSeek Harness for customer-feedback analysis.}

#Integrate your harness into your product backend with one API

Run product tasks with built-in or custom harnesses as pluggable agent backends. Call your self-hosted instance’s OpenAI Responses-compatible API and select the harness with metadata.harness_id. No Cloud deployment is required.

Once your harness runs successfully in the Console:

1. Open API Keys in the Console sidebar of the same CE instance (default local address) and choose Create API key.
2. Store the secret shown once as HARNESSROUTER_API_KEY in your product backend. Never expose it in browser code. This CE-issued key is separate from your Console password and provider key.
3. Call the API with the Harness ID shown in the Console and a model served by your connected provider.

export HARNESSROUTER_BASE_URL=http://localhost:3000/api/harness

curl --fail-with-body -sS "$HARNESSROUTER_BASE_URL/v1/responses" \
  -H "Authorization: Bearer ${HARNESSROUTER_API_KEY:?}" \
  -H 'content-type: application/json' \
  -d '{
    "input":"Reply with exactly: it works.",
    "metadata":{"harness_id":"codex"},
    "model":"gpt-5.4-mini",
    "stream":false
  }'

The task and its transcript appear in the same workspace in the Console. Set "stream": true to receive server-sent events.

The default URL works when your backend and CE run on the same computer. From another machine or container, use a reachable URL for the CE instance. Read the complete self-hosted API and networking guide →

#Agent harnesses as pluggable backends for your product

Power agentic features in your product with agent harnesses, including knowledge-work tasks such as creating content and analyzing data. Explore these ready-to-use kits to see harnesses in action as pluggable backends.

Explore the Starter Kits →

Setup notes & licensing

Start: Open Starter Kits in the Console and select a harness and model supported by your connected providers.

Dashboards: use a reachable database and a read-only database account. Set HR_SECRET_KEY to encrypt stored connections, and review the sample-row setting before connecting.

Licensing: Starter Kits use different terms from Community Edition.

Setup guide →

#Deployment choices

#Self-host for control

• Your infrastructure. One Docker deployment for the Console, Gateway, and Runner.
• Your credentials and state. Provider keys, sessions, files, and workspaces stay under your control. Model requests still go to your configured provider.
• Real workspaces. Native filesystem, shell, and Git workflows, with separate session workspaces.
• No Console product analytics. Community Edition disables the Console analytics pipeline.

#Choose your path to Cloud

Choose HarnessRouter Cloud for managed deployment, maintenance, and scaling, with tasks running in serverless, isolated sandboxes through the same API contract.

For local uploads: set HR_SECRET_KEY on your local instance to encrypt the saved destination key. Save your custom harness in Settings, select Upload to Cloud, then connect a destination using its Cloud workspace API key.

Uploads copy harness configuration, not provider keys, sessions, or generated files. Uploading again replaces that destination’s hosted copy.

#Inside Community Edition

┌─ HarnessRouter container ─────────────────────────────────┐
│  Console :3000   ← only published port                    │
│       │ same-origin proxy                                 │
│       ▼                                                   │
│  Gateway :8080   Responses API + harness lifecycle        │
│       │ loopback                                          │
│       ▼                                                   │
│  Runner  :8081   runs harnesses in session workspaces     │
│                                                           │
│  /data volume   database · files · secrets · workspaces   │
└───────────────────────────────────────────────────────────┘

The Gateway and Runner listen on loopback inside the container. Sessions use separate workspaces and operating-system users, not separate containers. The Console is the entry point for both UI and API.

See configuration, upgrades and backups, and public deployment with TLS.

#The Unified Harness Protocol

Unified Harness Protocol (UHP) is the public, versioned contract implemented by Community Edition and HarnessRouter Cloud. Its task surface is deliberately compatible with the OpenAI Responses API, so existing Responses SDKs, streaming parsers, and UI components can work with a UHP server. UHP defines harness execution semantics for harness selection, persistent sessions, files, cancellation, and harness-managed tools and skills.

This repository contains the Apache 2.0 reference implementation, machine-readable schemas, and the conformance suite.

#Resources

#Star History

#License

HarnessRouter Community Edition is licensed under Apache 2.0. Agent harness CLIs are installed on first launch and remain subject to their respective upstream licenses. See NOTICE for third-party notices and the Starter Kits repository for its separate licensing terms.

HarnessRouter is the world's first unified interface for agent harnesses.