HarnessRouter: Unified interface for agent harnesses
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…
HarnessRouter: Unified interface for agent harnesses launched on August 17, 2026 with 10 votes, #1,032 of 23,274 launches that month and more than 90% of that year's launches.
In plain words
HarnessRouter is a unified API that lets developers run multiple AI agent systems—including Codex, Claude Code, and Hermes—through a single interface. The self-hosted Community Edition implements the Unified Harness Protocol, an open standard, and handles sessions, streaming, file management, and error handling. It's designed for product teams who want to leverage best-in-class agent harnesses from frontier labs and open-source communities without building their own infrastructure, using their own infrastructure and API keys.
written from the facts on this page · September 2026
From the sources
HarnessRouter Community Edition: the self-hosted, Apache-2.0 edition of the unified interface for agent harnesses. Run Codex, Claude Code, Hermes, PI, DSH, and more through one API, with sessions, streaming, files, cancellation, and failure handling. Implements the Unified Harness Protocol (UHP), an open standard. Your keys, your infrastructure. - HarnessRouter/harnessrouter
In the maker’s words, at launch
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…
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