DeepSeek Harness: Open-Source AI Agent Framework — 2026 Guide
DeepSeek Harness (dsh) is the open-source agent runtime DeepSeek AI released on August 13, 2026 as a developer preview under the MIT license. It passed 90K GitHub stars within days and is positioned as the open alternative to Claude Code and OpenAI Codex.
🟢 Core idea — everything is a plugin: models, tools, skills, sessions, sandboxes, filesystems, agent loops, orchestration and even the UI are all swappable plugins built on the Cordis meta-framework. Mix, match, replace and extend any part without breaking the rest.
🟢 Install: requires only Node.js. Run npx @deepseek-ai/dsh web and open http://127.0.0.1:3080 — a local web UI starts immediately. Source at github.com/deepseek-ai/deepseek-harness.
🟢 Continuous session log: every prompt, tool call and result is recorded. Runs can be resumed, branched and replayed — useful for audits and debugging agent behaviour.
🟢 Model-agnostic: works with DeepSeek, OpenAI, Anthropic, GLM or any OpenAI-compatible provider. You pick the model that fits your budget and quality bar.
🟢 Minimal mode: strips the system down to shell + file editor — the same setup DeepSeek uses for its own benchmark runs.
🔴 Developer preview: the company explicitly warns "THERE WILL BE COMPATIBILITY-BREAKING CHANGES". Fine for experiments, demos and internal projects — not yet for critical client production.
🟢 License: MIT is permissive — commercial use, modification and distribution are allowed without forcing your changes to stay open.
🟢 UAE business angle: zero licensing cost for custom agents (reception, content, automation). Pay only for the model you use. Treat it as a prototyping platform until the API stabilises.
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