DeepSeek Harness vs Claude Code vs Omnigent

DeepSeek Harness vs Claude Code vs Omnigent: which one you need

DeepSeek Harness, Claude Code and Omnigent are all called agent harnesses, and they solve different parts of the problem. DeepSeek Harness is a plugin runtime with a web UI (user interface) where you supply the model. Claude Code is a terminal program from Anthropic that runs Anthropic models. Omnigent is an orchestrator from Databricks that drives other harnesses, including Claude Code, instead of implementing an agent loop of its own. None of them is a drop-in replacement for another, so the question worth answering is which layer you are missing.

The axes that actually differ are architecture, model coupling, interface, maturity and licence. Every version and date below was checked on 18 August 2026. Two of the three move fast enough that you should check again before you commit to one.

What is DeepSeek Harness, and what does the plugin model buy you?

DeepSeek published DeepSeek Harness, or dsh, at github.com/deepseek-ai/deepseek-harness in August 2026. The repository description states the whole design in four words: everything is a plugin. The model adapter, the tool registry, the session log, the sandbox and the agent loop itself are all plugins, loaded by a runtime built on Cordis. Adoption was unusually fast, and the repository passed 150,000 stars within days of publication (checked 18 August 2026).

DeepSeek Harness is currently in developer preview and is iterating rapidly. THERE WILL BE COMPATIBILITY-BREAKING CHANGES.

That is the README's own warning, and it is the most important sentence in this comparison. Anything you write against the plugin API (application programming interface) today is something you should expect to rewrite.

Start it with npx, which needs Node.js installed:

npx @deepseek-ai/dsh web

The command prints its URL. By default the web UI is served at http://127.0.0.1:3080. Building from source uses pnpm instead:

git clone https://github.com/deepseek-ai/deepseek-harness.git
cd deepseek-harness
pnpm install
pnpm run build
pnpm dsh web

dsh web is shorthand for dsh --profile web. A profile is a directory under $DSH_HOME/profiles/, and the launcher boots whichever one you name. That matters because there is a headless profile as well: dsh --profile headless "job" runs one persisted session, prints the result and exits, which is the shape you want in a cron job or a build step. Launcher flags such as --profile and --patch must come before the application's own arguments, because the launcher stops parsing at the handoff. A flag like --port belongs to the booted profile, not to the launcher, so its position matters. Plugins are managed by forwarding arguments to pnpm, as in dsh plugin --profile web add <package>.

What is Claude Code, and why is it a terminal program?

Claude Code is Anthropic's own CLI (command line interface) agent. There is no web UI in the product itself. It runs in your terminal, in the directory you want it to work on, which is why it fits a server session so well. Installation is one command on macOS, Linux and WSL:

curl -fsSL https://claude.ai/install.sh | bash
claude --version

A working install prints a version and the product name, for example 2.1.211 (Claude Code). If that fails, claude doctor prints read-only installation and settings diagnostics without starting a session. There is an npm package too, npm install -g @anthropic-ai/claude-code, which as of v2.1.198 wants Node.js 22 or later. It installs the same native binary, so the installed claude does not use your Node.js at runtime. Anthropic also publishes signed apt, dnf and apk repositories for Debian, Ubuntu, Fedora, RHEL and Alpine, which is the better choice on a server you manage with configuration management, because updates then arrive through your normal upgrade workflow.

Claude Code requires a Pro, Max, Team, Enterprise or Console account. The free Claude.ai plan does not include access. Deciding between a Claude subscription and API billing changes what you pay far more than any setting inside the tool does.

What is Omnigent, and what does a meta-harness orchestrate?

Databricks announced Omnigent in June 2026 and released it under the Apache 2.0 licence. It calls itself a meta-harness. It does not implement an agent loop. It drives the ones that already exist: Claude, Codex, Cursor, OpenCode, Hermes, Pi and OpenAI's agents SDK (software development kit). Several of those appear twice in the harness list, once in a form that talks to the vendor's SDK and once in a native form that wraps the vendor's real terminal program.

An agent is a YAML file, YAML being a plain text configuration format:

name: my_agent
prompt: You are a helpful data analyst.

executor:
  harness: claude-sdk

tools:
  word_count:
    type: function
    callable: mypackage.mymodule.word_count
  docs:
    type: mcp
    url: https://example.com/mcp
  researcher:
    type: agent
    prompt: Search for relevant information.

The executor.harness line is the point of the whole project. Change claude-sdk to codex and the same prompt with the same tools runs on a different vendor. A tool is a Python function, an MCP (model context protocol) server, or another agent, and that last case is how multi-agent work is expressed: a sub-agent is simply a tool. If you have not settled where skills, MCP servers and rules files each belong, the difference between agent skills, MCP and rules files is worth reading first, because Omnigent inherits whichever of those the harness underneath supports.

The shipped example makes the idea concrete. Polly is a coding orchestrator that writes no code itself. It plans, delegates work to coding sub-agents in parallel git worktrees, then routes each diff to a reviewer running on a different vendor's model.

Install it with the published script:

curl -fsSL https://raw.githubusercontent.com/omnigent-ai/omnigent/main/scripts/install_oss.sh | sh

Or install it manually, which needs Python 3.12 or newer:

uv tool install omnigent
omnigent setup
omnigent start

pip install "omnigent" works as well, and extras are selected the usual way with uv tool install "omnigent[databricks,modal]". omnigent setup collects credentials and defaults. omnigent start starts the server, registers the machine as a host, and serves a web UI on http://localhost:6767. omnigent server status and omnigent stop are the other two commands you will use daily. A bare omnigent opens an interactive session without starting the server.

The dependency list is longer than the one-line installer suggests: Python 3.12 or newer, git, Node.js 22 LTS (long term support) or newer with npm and pnpm, tmux for the native terminal wrappers, and bubblewrap (bwrap) for the Linux sandbox. That is a direct consequence of the design. Omnigent has to install and supervise the vendor CLIs itself, so it is Python software whose job is to run Node.js software.

Who supplies the model, and who pays for it?

This is the axis with the largest practical consequences, and the three answers are genuinely different.

DeepSeek Harness is bring-your-own. The installed provider catalogue covers Anthropic, OpenAI, Bedrock, Vertex, Azure and Codex. A custom provider entry takes a lowercase provider id, a display name, a base URL, an API protocol, a credential and at least one model, which is how you point it at a company gateway or a self-hosted server. Keys are written to $DSH_HOME/.credentials.yaml, and $DSH_HOME/settings.yaml keeps only a reference to them, which means the settings file is safe to share and the credentials file is not. A gateway entry can name an environment variable instead, with a line such as apiKeyEnv: GATEWAY_API_KEY. Despite the project name, nothing in it forces you onto DeepSeek's own models.

Claude Code is coupled to one vendor by design. You log in with a paid account, or you set ANTHROPIC_API_KEY and Claude Code prompts you once to approve that key instead of opening a browser. That second path is the one that works on a headless server. Organisations that already buy capacity elsewhere can route through Amazon Bedrock, Google Cloud's Agent Platform or Microsoft Foundry.

Omnigent needs whatever the harness underneath needs, gathered by omnigent setup. It accepts API keys, existing CLI subscriptions, OpenAI-compatible or Anthropic-compatible gateways, and Databricks workspaces. That is the real cost of a meta-harness: one machine ends up holding every vendor's credentials. Read how to keep secrets out of an AI agent's reach before that machine goes anywhere near the public internet.

How mature is each one, as of August 2026?

Claude Code has been generally available since 2025 and is on the 2.1.x line as of August 2026. It auto-updates in the background, offers latest and stable release channels, publishes GPG-signed release manifests, and documents a minimumVersion pin for organisations that need a floor. That is the profile of a product people already run in production.

Omnigent has been public since June 2026, is still in the 0.x series, and its README describes it as alpha. Expect both the harness list and the YAML schema to keep moving. It is usable, and it is not yet stable.

DeepSeek Harness is the youngest by a wide margin. It was published in August 2026, days before this comparison was written, and its own README promises compatibility-breaking changes. A very large star count tells you many people are watching it. It tells you nothing about whether the plugin API has settled.

What licence does each one carry?

DeepSeek Harness is MIT, with third-party licences disclosed in THIRD_PARTY_NOTICES.md. Omnigent is Apache 2.0. Claude Code is not open source: it is Anthropic's commercial product, and running it requires a paid account or billed API access. If your requirement is that you can read and patch every line, Claude Code is ruled out before any feature comparison begins. If your requirement is that the tool keeps working next month without your attention, that requirement points the other way.

What does it take to run each one on a VPS?

Claude Code is the simplest of the three. Install it, log in, and run it inside tmux so the session survives a dropped SSH (secure shell) connection. Anthropic documents 4 GB of RAM (random access memory) or more and an x64 or ARM64 processor, on Ubuntu 20.04 or later, Debian 10 or later, or Alpine 3.19 or later. On Alpine you also need bash, curl, libgcc, libstdc++ and ripgrep installed first, because the install command fails with a not found error without them. Running Claude Code on a VPS inside tmux covers the session handling in detail.

DeepSeek Harness needs Node.js and a browser pointed at its web UI. The README asks for Node.js without naming a minimum version, so Node 22 LTS is the safe pick, since that is what the surrounding ecosystem targets. Do not publish port 3080. Leave the server on 127.0.0.1 and forward the port from your laptop:

ssh -N -L 3080:127.0.0.1:3080 you@your-vps

Then open http://127.0.0.1:3080 locally. A full DeepSeek Harness install on a VPS covers the profile layout and the plugin commands.

Omnigent is the heaviest, because it installs and supervises other people's CLIs. It wants Python 3.12, Node.js 22, npm, pnpm, tmux and bubblewrap on the same box, and it will pull down each vendor CLI you enable on top of that. Forward its port the same way:

ssh -N -L 6767:127.0.0.1:6767 you@your-vps

For a server other people use, the supported path is the Docker deployment under deploy/, which enables multi-user accounts by default. The same behaviour is available on a manually started server by setting OMNIGENT_AUTH_ENABLED=1, and OIDC (OpenID Connect) login works against Google, GitHub, Okta and Microsoft. The Omnigent multi-agent harness guide covers the sandbox providers, which start to matter as soon as agents write to disk.

Why is the web UI blank on your server's public IP address?

Both web harnesses listen on loopback by default, and the obvious move is to bind them to 0.0.0.0 and open the port. Two separate things break. The first is security: neither ships authentication in its default local mode, so an open port is an open shell on your VPS. The second is a browser rule that surprises people. crypto.randomUUID() is only defined in a secure context, which means HTTPS (hypertext transfer protocol secure), localhost or 127.0.0.1. Load the same UI over a plain address such as http://203.0.113.10:3080 and the browser console reports:

TypeError: crypto.randomUUID is not a function

The page then renders partly or not at all, because session creation fails before anything can be drawn. Nothing is broken on the server, and the logs will show a normal request. The origin is not trusted by the browser, so a function the front end depends on was never defined. An SSH tunnel fixes this with no certificate, because 127.0.0.1 counts as a secure context. A reverse proxy holding a real TLS (transport layer security) certificate fixes it too, and then you have to add authentication yourself.

Which one fits you?

Pick Claude Code if you want a coding agent that works today, you are willing to pay Anthropic, and the terminal is where you already work. It is the only one of the three that is a finished commercial product rather than a preview.

Pick DeepSeek Harness if the plugin model is the point: you want to replace the model adapter, the sandbox or the agent loop, and you accept that the interface you write against will change. Its provider catalogue covers Anthropic and OpenAI, so choosing it is a bet on the runtime, not on DeepSeek's models.

Pick Omnigent if you already run more than one agent CLI and your actual problem is coordination: policy, sandboxing, review by a second vendor's model, and a shared session other people can watch. It adds a layer to your stack, and a layer you do not need is a layer that can break.

If you are still shortlisting, the Mimo Code AI coding agent sits in the same terminal-agent category as Claude Code, and running coding agents in a disposable VM is worth reading whichever one you choose, because none of these three makes a careless rm -rf safe on its own.

FAQ

Do I need a paid Anthropic plan to use Claude Code?

Yes. Claude Code requires a Pro, Max, Team, Enterprise or Console account, and the free Claude.ai plan does not include access. On a headless VPS, set ANTHROPIC_API_KEY before the first run: Claude Code then prompts you once to approve that key instead of trying to open a browser. Organisations with capacity elsewhere can point it at Amazon Bedrock, Google Cloud's Agent Platform or Microsoft Foundry instead.

Can DeepSeek Harness run Claude or OpenAI models?

Yes. The installed provider catalogue covers Anthropic, OpenAI, Bedrock, Vertex, Azure and Codex, and you add a key per provider under Settings then Models. Anything outside the catalogue goes in as a custom provider, which needs a lowercase provider id, a base URL, an API protocol, a credential and at least one model. Keys are stored in $DSH_HOME/.credentials.yaml while $DSH_HOME/settings.yaml holds only a reference, so back the credentials file up separately and keep it out of version control.

Does Omnigent replace Claude Code?

No. Omnigent runs Claude Code. Its harness list includes Claude, Codex, Cursor, OpenCode, Hermes and Pi, and an agent selects one with a single harness: line in its YAML file. You still install and authenticate the underlying CLI yourself. Omnigent adds orchestration, policy and sandboxing above that, so it earns its dependencies only when you are running more than one agent or more than one vendor.

Why is the DeepSeek Harness web UI blank on my server's public IP address?

Because a plain HTTP origin is not a secure context, crypto.randomUUID() is undefined there, and the browser console reports TypeError: crypto.randomUUID is not a function. Session creation fails, so the page renders partly or not at all while the server logs look normal. Forward the port over SSH with ssh -N -L 3080:127.0.0.1:3080 you@your-vps and open http://127.0.0.1:3080, since loopback counts as a secure context. A reverse proxy with a real TLS certificate also works, and then you must add authentication yourself.

How much RAM does a VPS need for these harnesses?

Anthropic documents 4 GB or more for Claude Code. Neither DeepSeek Harness nor Omnigent publishes a figure, so measure rather than guess. The model runs remotely in all three cases, so the harness itself is doing process supervision and file work rather than inference. What really sets the size of the box is the work the agent performs on it, such as a build and a test suite. Omnigent asks for the most, because Python, Node.js, tmux and every vendor CLI you enable run on the same machine.