omnigent
Reduces friction when integrating multiple AI coding agents into production workflows by centralizing orchestration, policy enforcement, and sandbox manageme…
Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device.
- Orchestrate multiple AI coding agents to work on a single complex software project simultaneously.
- Enforce security policies and sandboxing rules across different AI agents without rewriting their code.
- Switch between Claude, Cursor, and custom agents for the same task without changing your workflow.
Reduces friction when integrating multiple AI coding agents into production workflows by centralizing orchestration, policy enforcement, and sandbox management—avoiding costly rewrites when switching providers or scaling collaboration.
Engineering teams managing multiple AI coding tools who need unified orchestration, consistent policy controls, and cross-device collaboration without vendor lock-in.
https://github.com/omnigent-ai/omnigent
By omnigent-ai
How to Get It
claude plugins install omnigent-ai/omnigent
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me orchestrate multiple AI coding agents to work on a single complex software project simultaneously
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 7,870 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 7,870 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.