ScriptsJul 5, 2026·3 min read

Omnigent — Open-Source AI Agent Orchestration and Meta-Harness

Open-source framework for orchestrating multiple AI coding agents across harnesses with policy enforcement, sandboxing, and real-time collaboration.

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Ready-to-run agent install

This asset can be installed after the agent chooses its runtime, checks the plan, and runs the matching command.

Native · 98/100Policy: allow
Agent surface
Any MCP/CLI agent
Kind
Skill
Install
Single
Trust
Trust: Established
Entrypoint
Omnigent Overview
Direct install command
npx -y tokrepo@latest install f030a3bd-7808-11f1-9bc6-00163e2b0d79 --target codex

Run after dry-run confirms the install plan.

Introduction

Omnigent is an open-source AI agent framework that acts as a meta-harness, letting you orchestrate agents from different providers (Claude Code, Codex, Cursor, and others) through a unified interface. It adds governance, sandboxing, and collaboration capabilities on top of existing agent runtimes.

What Omnigent Does

  • Orchestrates multiple AI coding agents from a single control plane
  • Enforces policies and permissions across all agent actions
  • Provides sandboxed execution environments for safe code generation
  • Enables real-time collaboration between human developers and AI agents
  • Swaps between different agent harnesses without rewriting workflows

Architecture Overview

Omnigent sits between the user and one or more agent harnesses, intercepting tool calls and applying policy checks before execution. It uses a plugin architecture where each supported harness (Claude Code, Codex, etc.) is a swappable backend. A shared state layer enables multi-agent coordination on the same codebase.

Self-Hosting & Configuration

  • Install via pip with Python 3.10+
  • Configure agent backends through a YAML manifest file
  • Define policy rules for file access, network, and command execution
  • Set up team roles and permissions for collaborative sessions
  • Deploy the coordination server with Docker for multi-user setups

Key Features

  • Meta-harness design decouples workflows from any single agent provider
  • Policy engine enforces guardrails on file writes, shell commands, and network access
  • Sandboxed execution prevents accidental damage to production codebases
  • Multi-agent mode coordinates parallel agents working on different tasks
  • Real-time dashboard shows agent activity and resource usage

Comparison with Similar Tools

  • Claude Code — single-agent CLI; Omnigent orchestrates it alongside others
  • CrewAI — multi-agent framework focused on role-based collaboration
  • AutoGen — Microsoft's multi-agent conversation framework
  • LangGraph — graph-based agent orchestration for LangChain
  • OpenHands — standalone AI coding agent without cross-harness support

FAQ

Q: Which agent harnesses does Omnigent support? A: Currently supports Claude Code, OpenAI Codex, Cursor, Pi, and custom agents via the plugin system.

Q: Does Omnigent add latency to agent operations? A: Policy checks add minimal overhead (typically under 10ms per tool call). The agent runtime itself is the primary latency source.

Q: Can I use it for non-coding tasks? A: Yes. The orchestration layer works with any agent that uses a tool-calling interface, including research and data analysis agents.

Q: Is there a hosted version? A: Omnigent is self-hosted only. The project focuses on giving teams full control over their agent infrastructure.

Sources

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