HarnessRouter Community Edition

In plain words

HarnessRouter Community Edition is an open-source unified interface that lets developers integrate multiple AI agent harnesses—including Codex, Claude Code, and Hermes—into their products through a single API. Deployed on users' own infrastructure via Docker, it handles sessions, streaming, file management, and failure recovery while keeping model keys and data under user control. The community edition includes a gateway, runner, and console, requiring no external databases or cloud services, and allows switching between different agent harnesses without rebuilding backend code.

written from the facts on this page · September 2026

From the sources

Plug-and-play managed agent harnesses in your product: Codex, Claude Code and Hermes through one API on your infrastructure, now open sourced under Apache 2.0. Switch harnesses without rebuilding your backend. Sessions, streaming, files, artifacts, cancellation, failure recovery, all handled. Model provider keys, state, and deliveries under your control. Gateway, Runner, Console in one Docker container. Ready-to-use starter kit apps as inspiration of possibilities.

Plug Codex, Claude Code, and Hermes into your product through one Agent API on your own infrastructure. Explore Community Edition, UHP, and the Starter Kit.

Plug 26 agent harnesses, Codex and Claude Code to ZeroClaw and System One, into your product through one Agent API, on your own infrastructure. Apache 2.0 · One Docker container · Your keys, state, and files Gateway, Runner, and Console start together. No managed database, external vault, or cloud account required. The API, Console, SQLite state, and workspace files stay on the infrastructure you control. Integrate once, select the harness for each task, and switch without rebuilding your product backend. HarnessRouter handles the backend lifecycle around each harness, not only the initial model request. UHP is the public, versioned contract that makes harness implementations portable,…from harnessrouter.ai

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  Harness by Autonomous6d ago · autonomous.ai · ▲287

  Every coding agent, every machine, one command center.

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  HarnessRouter: Unified interface for agent harnessesAug 2026 · github.com · ▲10

  Hey HN! We are building HarnessRouter, a canonical API for running Codex, Claude Code, Hermes, and other managed agent harnesses as your product backend. Before building HarnessRouter, I used to build our own agent harness for our products. I tried LangGraph, agent SDKs from different vendors, pydantic, LLM tool use / function call, and so on. It's a very heavy lifting engineering effort, and I am disappointed about the agent deliveries compared to what Codex, CC can deliver. That changed my mindset. The frontier labs and famous open source communities are already putting so much…

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  Agent-harness-kit scaffolding for multi-agent workflowsMay 2026 · ahk.cardor.dev · ▲82

  A collection of open-source TypeScript tools by @enmanuelmag. heimdall-mcp for MCP proxy telemetry. agent-harness-kit for multi-agent orchestration.

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  AgentAPI – HTTP API for Claude Code, Goose, Aider, and Codex2025 · github.com · ▲163

  HTTP API for Claude Code, Goose, Aider, Gemini, Amp, and Codex - coder/agentapi

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  Smart model routing directly in Claude, Codex and CursorJun 2026 · github.com · ▲216

  We built a model router that plugs into coding agents (e.g. Claude Code, Codex, Cursor, etc.) and intelligently sends requests to the best model to serve them. Here's a quick demo of running it locally: https://www.youtube.com/watch?v=isKhAyivtfM. At Weave, we write most of our code with AI, and it's been getting more expensive. This came to a head when Opus 4.7 was released and, thanks to its tokenizer changes, our costs shot up. We knew we didn't need Opus for everything but we didn't want to lose out on the intelligence for the cases where you really need it. So we decided…

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  Skill that lets Claude Code/Codex spin up VMs and GPUsFeb 2026 · cloudrouter.dev · ▲138

  I've been working on CloudRouter, a skill + CLI that gives coding agents like Claude Code and Codex the ability to start cloud VMs and GPUs. When an agent writes code, it usually needs to start a dev server, run tests, open a browser to verify its work. Today that all happens on your local machine. This works fine for a single task, but the agent is sharing your computer: your ports, RAM, screen. If you run multiple agents in parallel, it gets a bit chaotic. Docker helps with isolation, but it still uses your machine's resources, and doesn't give the agent a browser, a desktop, or a GPU to…

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