Comparison

AI Commander vs Omnara

These two are neighbours rather than rivals. Omnara is an open-source platform for building and running your own AI agents: you pick the model, define the tools, and launch the agent from an API, a dashboard, Slack or a schedule, on sandboxes or your own machines. AI Commander is not an agent and has no chat app of its own; it lets the AI client you already use — Claude, ChatGPT, Codex or Grok — run commands and long jobs on computers you own, Windows desktops included. Both reach those computers over an outbound connection, which is where the overlap starts and mostly ends.

Verified 2026-10-23 Every Omnara claim below was checked against their own site, docs, repository and pricing page — listed under Sources.

The short answer

Use Omnara when you are building an agent — one that runs as a service for your users or your team, started from your product, Slack, Discord, GitHub or a cron schedule, on a model you choose, with per-tool approvals and agent state handled by the platform, and optionally self-hosted under Apache 2.0. Use AI Commander when you already have the AI you want to talk to and need it to act on your own machines: a Windows PC, a Mac, a Linux server or a GPU box, reached from your existing Claude, ChatGPT, Codex or Grok conversation, with long jobs that keep running after the chat ends. If you are not writing agent configs, Omnara is probably more platform than you need; if you are, AI Commander does not replace it.

A note on history: Omnara's earlier launches, listed on its Y Combinator company page, presented it as a way to "Run Claude Code from Anywhere" across "terminal, web, and mobile". Its current site, docs and README (checked 2026-10-23) describe the agent platform below and do not mention a mobile app, so this page compares the product as it is described today.

What each one is

Omnara

In its own words, "the open-source managed agent platform" and "a self-hostable alternative to Claude Managed Agents and OpenAI's Agents API", offering "One API to deploy and run agents for your users and team, on any model, any machine, and any cloud." An agent starts as a YAML config — an instruction, a model, tools and the machines it may use — and is launched from the web dashboard, the REST API, the TypeScript SDK (@omnara/sdk), the omnara CLI or Omnara's MCP server. Every machine runs a small daemon, omnarad, which "connects outbound to the control plane", with no inbound ports or SSH keys; the README says to install it on "any macOS or Linux laptop, VM, or container", or to use on-demand sandboxes from a list of providers. Agents live in the control plane as event logs rather than on a machine, each tool can be set to run immediately, ask a person first or be blocked, and Slack, Discord and GitHub integrations start agents from those places. It is Apache 2.0 and runs either as Omnara Cloud or self-hosted with Docker Compose.

AI Commander

A hosted relay plus a small agent per machine, reachable as an MCP server and as a plain REST API. It brings no model and no chat window: the AI client you already use is the interface, and AI Commander is the hands on your machines. The agent holds one outbound WebSocket open, so there is no inbound port, no exposed SSH and no VPN, and it runs on macOS, Windows and Linux. On top of that it adds detached jobs with a full lifecycle (remote_job_start, _status, _logs, _cancel) that outlive the call and the conversation, NVIDIA GPU discovery with exclusive per-job reservation, per-account machine notes kept on the box, a file courier, and opt-in screenshots on desktop macOS and Windows.

Side by side

	AI Commander	Omnara
What it is	A connector: your existing AI client runs commands and long jobs on machines you own	"The open-source managed agent platform" for deploying and running your own agents
Where you talk to the AI	In the client you already use — Claude, ChatGPT, Codex, Grok or any MCP client. No app of its own	Omnara's dashboard, CLI chat, your own app via API/SDK, or Slack, Discord and GitHub
Model	Whatever model your AI client runs; AI Commander supplies none	"Any compatible model": your own keys for OpenAI, Anthropic, OpenRouter and others, or Omnara-managed models
Connection direction	✓ Agent dials out over one WebSocket; no inbound port, no SSH, no VPN	✓ The `omnarad` daemon "connects outbound to the control plane"; no inbound ports or SSH keys
Operating systems for your own machines	macOS, Windows and Linux, desktops included	"any macOS or Linux laptop, VM, or container"; Windows not documented
Cloud sandboxes on demand	✗ Machines you own or rent and install the agent on	✓ Machine pools from sandbox providers such as Daytona, E2B, Modal and Unikraft Cloud
Per-tool approvals	✗ No approval step of its own; any confirmation comes from your AI client's tool-permission prompt	✓ Each tool can "run immediately, ask a person first, or be blocked"
Slack, Discord, GitHub, schedules	✗ Not part of the product	✓ Integrations plus cron triggers with time zones
Self-hosting	✗ Hosted relay only	✓ Apache 2.0; Docker Compose self-host
Work that outlives the conversation	✓ Detached jobs with start / status / logs / cancel, surviving the call, the client and the chat	✓ Agents "live in the control plane as event logs"; "the machine does not own the agent"
GPU discovery & reservation	✓ NVIDIA cards per machine with model, VRAM and utilisation; `gpu_index` reserves one exclusively, a second job is refused with `gpu_busy`	not documented as a feature; the README mentions using several machines at once, "for example, a set of GPU servers"
Desktop screenshot	✓ On desktop macOS and Windows, opt-in by the machine's owner	not documented
MCP	Is an MCP server (plus a REST API) your AI client connects to	Agents can use MCP servers as tools; Omnara also runs its own MCP server for launching and managing agents
Price to start	Free up to 10 saved machines	"$0 platform fee"; free with your own model keys and machines, pay as you go for Omnara-managed ones

"not documented" means exactly that: we read the sources listed below on 2026-10-23 and found no statement either way. It is not a claim that the feature is absent, and we make no claims at all about the other project's security, reliability or roadmap.

Where AI Commander is different, concretely

Nothing new to talk to. You keep using Claude, ChatGPT, Codex or Grok. AI Commander adds an MCP server (or a REST endpoint) to that client, so the conversation, the model and the history stay where they already are. There is no agent config to write.
Windows and Mac desktops, not only servers. The agent runs on Windows, macOS and Linux, and can take a screenshot of a desktop if the machine's owner opts in — so a gaming PC, a work laptop and a rack server are addressed the same way in one conversation.
Short work and long work are different tools. A command is capped at 1 hour of wall clock, which is a hard kill, and 1 MiB of output, which truncates the reply. A detached job returns a job id immediately and keeps running after the call returns, after the client disconnects and after the conversation ends; you check status, read logs or cancel it by id from a new chat. It also survives the agent itself restarting: on Linux each job is launched into its own transient systemd scope, outside the agent service's control group, so restarting or upgrading the agent leaves it running — that needs a systemd host with the agent running as root, and without both a restart still ends running jobs.
GPUs are reserved, not shared by accident. Each machine reports its NVIDIA cards with model, VRAM and utilisation. Passing gpu_index holds one card exclusively for the job; a second job asking for it is refused with gpu_busy.
Agent to agent. One of the things you can start on another machine is a coding agent — see remote coding agents — and collect the result later by job id.
Commands are not kept. Command text and stdout/stderr pass through the relay's memory and are discarded — never written to logs or a database. See the privacy policy.

Price

AI Commander's Free plan is AI access to your computers, up to 10 saved machines. Pro is $49 per month and covers every saved machine up to a technical 100-machine ceiling*, plus file transfer with remote_pull and remote_push. Your AI client's own subscription is separate. Full detail on our pricing page.

On the Omnara side, checked 2026-10-23: the self-serve plan has a "$0 platform fee" with "no per-seat fees"; you can "Bring your own model keys for free" and "Connect your own machines for free", or pay for Omnara-managed models "at provider token rates" and Omnara-managed machines at "$0.0414 per GiB of memory per hour online" plus "$0.20016 per GiB of memory per 30 days retained". Omnara's own example: "A 4 GiB machine active one hour a day costs about $5 a month in runtime plus $0.80 in retention." Self-hosting is free under Apache 2.0, and Enterprise is priced on request. The two are billed for different things — Omnara for compute and tokens it manages, AI Commander as a flat monthly plan per account — so the totals are not directly comparable.

* 100 machines is a technical ceiling, not a policy limit. Need more? Get in touch — we'll sort it out.

When NOT to use AI Commander

Pick Omnara instead if:

You are building an agent for your users or your team — in your product's dashboard, in Slack or Discord, on GitHub pull requests — rather than chatting with one yourself; AI Commander has no agent loop, no integrations and no API for launching agents.
You want to choose the model per agent, including models you host yourself; AI Commander uses whatever your AI client runs and supplies no model.
You need per-tool approvals enforced by the platform, so a person must approve a call before it runs; AI Commander has no approval step of its own.
You want disposable cloud sandboxes created on demand instead of machines you own; AI Commander only reaches computers you install its agent on.
You need to self-host the whole control plane: Omnara is Apache 2.0 with a Docker Compose deployment, while AI Commander's relay is hosted and has no self-hosted option.

Omnara →

When AI Commander fits

You already work in Claude, ChatGPT, Codex or Grok and want it to act on your machines without adopting a new app.
The machine is a Windows PC or a Mac on your desk, not only a Linux server.
The work is long: a training run, a build or a dataset pass that must survive the chat ending.
There is a GPU to discover and hold exclusively while a job runs.
You want no agent configs, no model keys and no platform to operate — install the agent, connect your client, ask.

FAQ

What is Omnara now?

As of 2026-10-23, Omnara describes itself as "the open-source managed agent platform" and "a self-hostable alternative to Claude Managed Agents and OpenAI's Agents API". You define an agent in a YAML config, pick any compatible model, and launch it through a web dashboard, a REST API, a TypeScript SDK, a CLI or an MCP server; each machine the agent uses runs the omnarad daemon, which connects outbound. The code is Apache 2.0 on GitHub. Its earlier launches, listed on its Y Combinator company page, presented it as a way to "Run Claude Code from Anywhere" across "terminal, web, and mobile"; its current site, docs and README do not mention a mobile app.

What is the difference between AI Commander and Omnara?

They sit in different layers. Omnara is a platform for building and running your own agents: it supplies the agent loop, agent state, model providers, tool permissions, sandboxes and Slack, Discord and GitHub integrations. AI Commander is not an agent and has no chat app of its own: it is an MCP server and REST API that lets the AI client you already use (Claude, ChatGPT, Codex, Grok or any MCP client) run commands and long jobs on machines you own. Both reach machines over an outbound connection, so neither needs inbound ports or SSH keys.

Can I use AI Commander and Omnara together?

Yes, in principle, because both speak MCP. Omnara documents connecting MCP servers to its agents, and AI Commander is an MCP server at https://aicommander.dev/mcp, so an Omnara agent could be given AI Commander as a tool to reach a Windows or macOS desktop. We have not tested that combination, so treat it as a possibility rather than a supported setup.

When is Omnara the better choice?

When you are building an agent product or an internal agent service rather than working in your own chat: agents started from your app, Slack, Discord, GitHub or a schedule; a model you choose per agent; per-tool approvals enforced by the platform; on-demand sandboxes from cloud providers; or a control plane you self-host under Apache 2.0. AI Commander provides none of those, and it has no self-hosted option.

Which one lets Claude or ChatGPT run commands on my own Windows PC?

AI Commander. Its agent runs on Windows, macOS and Linux, and you connect it to the AI client you already use with a session code or an API key, with no new app to adopt. Omnara's README says to install its daemon on "any macOS or Linux laptop, VM, or container" and does not mention Windows, and in Omnara the conversation runs in Omnara's own agent loop rather than in your Claude or ChatGPT chat.

Sources & verification

Omnara facts on this page were read from the project's own site, docs and repository on 2026-10-23:

Positioning ("The open-source alternative to Claude Managed Agents", "One API to deploy and run agents for your users and team, on any model, any machine, and any cloud.")omnara.com
Pricing: "$0 platform fee", own model keys and machines free, managed models at provider token rates, machines "$0.0414 per GiB of memory per hour online" and "$0.20016 per GiB of memory per 30 days retained", the 4 GiB example, Enterprise on requestomnara.com/pricing
"the open-source managed agent platform", YAML agent configs, dashboard / API / SDK / CLIdocs.omnara.com/introduction
omnarad "connects outbound to the control plane"; "the machine does not own the agent", agents "live in the control plane as event logs"; BYO machines and sandbox poolsdocs.omnara.com/machines/overview
Per-tool permissions; MCP servers as agent tools (MCP tools default to asking first)docs.omnara.com/tools/permissions
Earlier launches: "Run Claude Code from Anywhere", "terminal, web, and mobile" (listed under Previous Launches)ycombinator.com/companies/omnara
README: Apache 2.0, Docker Compose self-host, daemon on "any macOS or Linux laptop, VM, or container", "Any compatible model", "a set of GPU servers", Slack/Discord/GitHub, cron triggers, MCP server at app.omnara.com/mcp; latest daemon release omnarad v0.2.9 (2026-10-21)github.com/omnara-ai/omnara

AI Commander facts trace to llms.txt, the docs, file transfer, the privacy policy and the plan limits in the relay's own entitlement code.

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