One API for agent backends
Run Codex, Claude Code, Hermes, and other supported agent setups behind your product through one API, so your app can request completed work without managing the backend pieces itself.
HarnessRouter
소유권 인증HarnessRouter is an AI agent API for product developers to add agent-backed features without building the backend layer. Server-side runs return reviewable diffs, files, documents, and more.
Overview
HarnessRouter is an AI agent API for product developers who want agent-backed features inside their own apps without building the backend layer from scratch. The site positions it as a way to run agent harnesses behind your product and return finished, reviewable work to your UI.
The product is built around bringing tools such as Codex, Claude Code, Hermes, and similar agent setups into a product through one API. Its documentation and homepage emphasize server-side integration, configurable harnesses, and outputs that can be shown to users as files, diffs, images, or other artifacts.
Core capabilities
Run-level tracing and review
Trace tasks step by step and inspect an execution overview, event timeline, and selected harness details to understand what the agent did during a run.
Configurable harness selection
Configure each harness when needed, and switch the named harness in config without changing your integration code or output schema, according to the source documentation.
Renderable artifact delivery
Return structured outputs that the UI can render and gate for user review, including diffs, files, documents, images, and confirmations from real tool actions.
Usage controls and spend caps
Use subscription credits first, then top up usage balance, with budgets, alerts, and hard caps to keep production agent spend under control.
Practical use cases
User-facing agent workflows
Build a product feature that accepts a user request and returns a finished artifact, such as a codebase, document, image, or video, for review inside your app.
Embedded agent backend
Add a server-side layer for teams that want Codex, Claude Code, or similar agents embedded in a product without managing the agent backend infrastructure themselves.
Progressive, reviewable task completion
Support a workflow where the user submits a task, the agent runs with tools and guardrails, and the product shows progress plus a reviewable result before the user accepts it.
Configurable agent routing
Run different harness configurations for different tasks or swap harnesses later when the product needs a different agent setup, while keeping the integration stable.
Managed production usage
Control production spend with plans, credits, top-ups, budgets, alerts, and hard caps when agent usage is part of a monetized product.
Pros and Cons
Pros
- Combines agent runtime pieces behind a product-facing API instead of requiring teams to build the backend layer themselves.
- Supports reviewable outputs that can be surfaced in a UI, rather than only returning chat-style text.
- Lets teams switch between named harness configurations without rewriting the integration code.
- Includes pricing controls such as credits, top-ups, budgets, alerts, and hard caps for production usage.
- Offers a quick-start flow that is aimed at coding-agent-assisted implementation.
Cons
- The public documentation shown here is still limited on supported integrations, models, and broader setup details.
- The source does not spell out every output type or workflow limitation, so readers may need to consult the docs before committing to a specific implementation.
FAQ
What is a harness in HarnessRouter terms?
HarnessRouter provides the execution layer around an agent. The source describes it as instructions, model policy, tools and MCP, skills, runtime and sandbox, permissions and guardrails, plus the output contract, so the model can do work and return artifacts instead of only text.
Why use HarnessRouter instead of calling Codex or Claude directly?
The product is positioned as a different layer from the model itself. The site says you should use Codex or Claude Code to build your app, while HarnessRouter brings those agent capabilities into your product so users can get finished work without opening a terminal.
How do you set it up?
The docs show a quick start where you copy the AGENTS.md guide into a coding agent, describe the feature you want, and then add a Workspace API key through a secure modal. The agent stores the key as HR_API_KEY and continues the build.
What comes back to my app?
The rendered output described on the site includes structured results such as reviewable diffs, generated files and documents, images, and confirmations of tool actions like GitHub, Slack, Notion, or internal APIs.
How does pricing work?
Pricing starts with a 7-day trial and then monthly platform plans. The pricing page says production usage draws from included credits first, then top-up balance, with budgets and hard caps to control spend.
Quick Facts
- Category
- AI agent API
- Primary users
- Product developers and teams building agent-backed features
- Delivery model
- Server-side agent backend layer
- Pricing model
- Paid subscription with 7-day trial and usage top-ups
- Source domain
- harnessrouter.ai
- Notable workflow
- Copy AGENTS.md, ask a coding agent to build, then add a Workspace API key securely
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