[opensourcedex]

Omnigent is a free, open source ai assisted coding project written in Python and released under Apache-2.0. It has 10,045 GitHub stars, 1,583 forks and 1,315 open issues, and was last pushed 3 hours ago. On this registry it ranks #16 of 24 tracked projects in AI Assisted Coding, with 5 head-to-head comparisons available. It gained 162 stars over the last 6 tracked days.

What is Omnigent?

What it is

Omnigent is an open-source AI agent framework and meta-harness in the Developer Tools and AI Assisted Coding ecosystem. It provides a common orchestration layer over Claude Code, Codex, Cursor, OpenCode, Hermes, Pi, and custom YAML agents. The Python project uses the Apache-2.0 license and combines different harnesses without rewriting the workflow.

The problem it addresses is fragmentation among AI coding agents, models, devices, and execution environments. A developer may need several agents in one session, handoff from the terminal to the browser or the phone, approval policies, spend caps, tool limits, and sandboxes. Omnigent presents these as one shared layer across each provider and host.

Key capabilities

  • Users can mix Claude Code, Codex, Cursor, OpenCode, Hermes, Pi, and custom YAML agents in one session, so one agent can review another or split a task.
  • Sessions can start in a terminal, continue in a browser, and resume on a phone or the macOS app, syncing messages, sub-agents, terminals, and files.
  • Model access can use first-party API keys, Claude or ChatGPT subscriptions, or compatible gateways, rather than only one model provider.
  • Teams can share a session to chat with an agent, watch it work live, co-drive a machine, or fork it.
  • Agents can run in cloud sandboxes such as Modal, Daytona, E2B, Kubernetes, Boxlite, microsandbox, or Databricks.
  • Policies can pause for approval before risky actions, cap spend, or limit tools across a server, an agent, or a chat.

Who uses it and how

  • Developers use Omnigent to supervise multiple coding agents in one workflow when different agents suit different parts of a task.
  • Teams use shared sessions so teammates can observe an agent, interact with it, co-drive a machine, or fork a conversation.
  • Self-hosters use Omnigent to run agents locally or in disposable cloud sandboxes, including Kubernetes and managed sandbox providers, with policies for approval, tool limits, and spend caps.

Getting started

The README describes a curl installer, optional extras, manual installation with uv or pip, and a Homebrew tap, requiring Python 3.12 or later and uv. Users can also install from the repository and download the macOS desktop app.

When to use it — and when not to

Omnigent is useful when a team needs one common layer for several agent harnesses, device handoff, shared sessions, policy enforcement, and sandbox execution. It is less suitable for a user who wants a single packaged coding agent, because the project is marked alpha, has a young repository age, lists zero contributors, and has 1,315 open issues. A self-hoster must operate Python 3.12, uv, model credentials or gateway access, and any selected sandbox, storage, or memory integrations.

project readme (upstream, from github) — read inline

Omnigent

The open-source meta-harness for all your AI agents.

Omnigent is an open-source meta-harness that gives you a common orchestration layer over Claude Code, Codex, Cursor, OpenCode, Hermes, Pi, and the agents you write yourself: swap or combine harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device — terminal, browser, phone, or the native desktop app.

PyPI version License: Apache 2.0 Discord Status: alpha

omnigent.ai · ⬇️ Download the macOS desktop app

The Omnigent desktop app: starting a new session, with pinned and project-grouped sessions in the sidebar

Why Omnigent?

Omnigent lets you:

  • 📱 Work with agents from any device, including your phone. Sessions follow you: start in your terminal, continue in the browser, pick it up on your phone. Messages, sub-agents, terminals, and files stay in sync.

  • 🤖 Supervise multiple agents. Mix Claude Code, Codex, Cursor, OpenCode, Hermes, Pi, and custom agents (defined in YAML) together in the same session. Ask one agent to review another's work, or split a task across agents that are each good at different things.

  • 🔌 Use any model. A first-party API key, a Claude/ChatGPT subscription, or any compatible gateway. All first-class.

  • 🤝 Collaborate. Share a session so teammates can chat with your agent and watch it work live, co-drive it on your machine, or fork the conversation to continue on their own.

  • ☁️ Run agents in cloud sandboxes. No laptop required: run sessions in disposable Modal, Daytona, Blaxel, Islo, E2B, CoreWeave, Kubernetes, OpenShell, Boxlite, microsandbox, or Databricks sandboxes, launched from the CLI or provisioned by the server per session (managed hosts).

  • 🛡️ Govern your agents. Create policies to pause for your approval before risky actions, cap spend, or limit which tools an agent reaches. They apply to the whole server, one agent, or a single chat.

Quick start

1. Install

One command installs Omnigent and everything it needs:

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

Need an optional integration? Pass one or more extras to the installer:

curl -fsSL https://raw.githubusercontent.com/omnigent-ai/omnigent/main/scripts/install_oss.sh | sh -s -- --extra databricks
curl -fsSL https://raw.githubusercontent.com/omnigent-ai/omnigent/main/scripts/install_oss.sh | sh -s -- --extra modal,e2b

Available user-facing extras include:

  • Model providers: databricks, bedrock, vertex
  • Sandbox providers: modal, daytona, blaxel, boxlite, microsandbox, cwsandbox, e2b, openshell, kubernetes
  • SDK harnesses: antigravity, copilot, cursor, agents-sdk
  • Storage and memory: s3, hindsight
Prefer to install manually?

Omnigent needs Python 3.12+. Install the omnigent package:

uv tool install omnigent        # or: pip install "omnigent"

Manual installs use the same extras syntax, for example:

uv tool install "omnigent[databricks,modal]"

Or with Homebrew:

brew install omnigent-ai/tap/omnigent

Or install straight from the repo:

uv tool install -q --python 3.12 git+https://github.com/omnigent-ai/omnigent.git
Toolchain and prerequisites (if the installer reports a missing tool)
  • uv (required). https://docs.astral.sh/uv/getting-started/installation/ The installer offers to set this up for you.
  • git (required).
  • Node.js 22 LTS or newer with npm (for the coding-harness CLIs installed by omnigent run) and pnpm (for the web UI). You can get both from a single Node install; pnpm is available via corepack enable or npm install -g pnpm.
  • Kiro CLI (optional), for omnigent kiro: install with curl -fsSL https://cli.kiro.dev/install | bash, then sign in with Kiro. Kiro tool approvals stay answerable in the embedded Terminal; supported one-time approvals also appear as Chat cards. See docs/kiro-native-elicitation.md.
  • tmux, required by the native omnigent terminal wrappers (claude, codex, cursor, hermes, kiro, pi) (brew install tmux / apt install tmux; the installer offers to install it for you).
  • bubblewrap (bwrap), Linux only. The native omnigent terminal wrappers and the pi harness wrap each agent terminal in a bwrap OS-sandbox; on Linux that isolation is mandatory, so a missing bwrap binary makes those terminals fail to start (apt install bubblewrap; the installer offers to install it for you). macOS uses the built-in seatbelt sandbox and needs nothing extra.
  • Databricks (optional). To use a Databricks workspace as your model provider, install Omnigent with the databricks extra: uv tool install "omnigent[databricks]" — or pass it to the bootstrap installer with ... | sh -s -- --extra databricks. Signing in to the workspace also uses the Databricks CLI.
Windows (native)

Omnigent runs natively on Windows in a degraded mode. The install_oss.sh bootstrap is POSIX-only, so install with uv directly:

uv tool install --python 3.12 omnigent
# or from the repo:
uv tool install --python 3.12 git+https://github.com/omnigent-ai/omnigent.git

What works on Windows: omnigent server, the web UI, and the SDK-based harnesses (omnigent run with the claude-sdk / cursor / codex harnesses). Agents run under a Windows Job Object for process-tree containment.

What is not available on Windows (use Linux/macOS, or WSL, for these):

  • the native omnigent claude / omnigent codex / omnigent cursor tmux/PTY terminal wrappers (run an SDK harness or the web UI instead);
  • bwrap/seatbelt filesystem & network sandboxing and the L7 egress proxy — the Job Object backend contains the process tree and enforces resource limits but does not isolate the filesystem or network.
Updating to a new release

When a newer release is on PyPI, Omnigent shows a one-line notice (once per release) pointing here. To update:

omni upgrade            # detects how you installed, drains & stops the local
                        # server, then runs the matching upgrade command
omni upgrade --check    # just report whether a newer release is available

omni upgrade waits for in-flight agent sessions to finish before stopping the local server (pass --force to stop them immediately); the next omni command brings the server back up on the new version. Source checkouts update with git pull instead. Silence the notice with OMNIGENT_NO_UPDATE_CHECK=1.

The check queries your configured package index — honoring UV_INDEX_URL / PIP_INDEX_URL and your uv.toml / pip.conf (default PyPI), so private mirrors work out of the box; override with OMNIGENT_INDEX_URL if needed.

Uninstalling Omnigent

Preview the CLI/profile cleanup that would run by default:

omnigent uninstall

Remove the CLI and installer-managed PATH entries while keeping your local history, credentials, and projects:

omnigent uninstall --yes

To also remove Omnigent state under ~/.omnigent, pass --purge; Omnigent backs it up outside the target before deletion. Your ~/omnigent workspace is kept unless you explicitly add --purge-workspace.

omnigent u

readme truncated — read the full docs on github

Frequently asked questions

Is Omnigent free to use?

Omnigent is open source under the Apache-2.0 licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does Omnigent do?

Common layer for composing and governing AI agents

What is Omnigent written in?

Omnigent is primarily written in Python. Its source is publicly available at https://github.com/omnigent-ai/omnigent, and it has 10,045 GitHub stars.