Havuz

Self-hosted coordination for AI workers: per-task graphs, device/model timelines, progress receipts, and source-aware usage. MIT.

Let Claude Code, Codex, OpenCode, Pi and other agents run DeepSeek Harness (dsh) sessions in parallel: research batches, material gathering,

Give AI agents ambitious work without losing the plot. nac is an open-source harness for long-running tasks, using a central orchestrator, t

Crossroad A2A: agent-to-agent mail so ChatGPT, Claude, Gemini, Codex and Grok agents work as one team across machines and SaaS apps. Open so

An AI workforce on your desktop. Describe the work; a team of AI agents does it in the open and hands it back checked. Any model, any harnes

Agents can work. They cannot declare success. A governed coordination protocol for multi-agent AI work: eight contracts (task, resource, own

Markdown-first orchestration for 71 specialists across Codex, Claude, Gemini, and Grok. Chrono coordinates scoped tasks in isolated git work

Multi-harness control protocol that turns requests into approved design contracts, orchestrating isolated worker sessions for sequential imp

Keep an eye on your AI coding agents: a live browser view of your agents, and CLI-based mail for them to collaborate on Tasks.

dsh-agent-team: Agent Teams for DeepSeek Harness. Hand work to a team of agents that carries it end to end while you set the direction and h

One Hermes conductor. Many coding CLIs. Zero trust in self-reports. Production multi-harness orchestration patterns: worktree lanes, verific

An agent design team you control: 10 agents that run an inclusive design process while you direct.

AtlasAgent - an auditable AI agent control plane: evidence-backed memory, governed tool runtime, checkpoint DAG recovery, and a 55-chapter e

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts

Open-source mission control for coding agents. Run cross-vendor workers in isolated worktrees, audit every submission, and revert an entire

AI agent team that takes an idea from research to launch, built on opencode. No framework, no extra dependencies.

One local board for Claude Code, Codex, Cursor and 5 more coding agents. See which session needs you, share your fleet card, start free on $

Testing and observability for multi-agent delegation, MCP tools, permissions, sandboxed actions, prompts, and workflow replay.

A desktop app for running coding agents side by side in project-based terminal sessions.

Kether-governed AI agent orchestration with Pi/MCP, isolated workers, LSP tools, and a portable Windows/WSL2 installer

Top AI Router 2026: Split Codex for Quick Code & Claude for Complex Refactoring

Open-source canvas for orchestrating Claude Code, Codex, and other CLI agents. Run agents in parallel, delegate tasks, and let AI build reus

Hive compute for coding agent swarms - expand your personal compute by adding on-demand agentic swarms

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

The all-in-one AI workforce platform, to build AI agent teams. You are the boss.

Make Opus 4.8 (or any Claude model) work like Claude Fable 5 — a Claude Code skill + guard hooks (plan gate, model ceiling, per-task enforce

General agent written in go for lighter , faster and more token efficent sessions. Agents no longer iterate mindlessly even after making via

A native Rust CLI for orchestrating AI agents across projects, with persistent sessions, worktrees, and local-first control.

面向企业研发团队的多人、多 AI Coding Agent 协作控制平台。以人为责任主体，以 Agent 为执行代理，通过统一任务、上下文、事件与成果协议连接不同 AI 客户端。

Open-source multi-agent coding CLI for the terminal (TypeScript, MIT). Switch models mid-session; finish goals only when your test passes.

Agents you can inspect, replay and trust. An agent framework for TypeScript and Python, built on an append-only event log.

A task conductor for Claude Code that gets better the more you use it. Multi-agent orchestration with an evidence contract that BLOCKS inste

Self-hosted workflows for coding-agent delivery. Orchestrate CodeBuddy, Codex and Claude Code with scripts and human approval gates. Include

Open-source skills for Claude Code and Codex, with an MCP server, a PyPI package and Suede Awesome Everything, a directory that scores AI ag

Multi-model delegation for Codex: native and ACP workers, main-session context separation, and a local Dispatch dashboard.

One CLI to orchestrate them all. Manage a team of AI agents executing tasks in parallel from your terminal using a command line interface to

Synchronize and Orchestrate agents from CLI to GUI, across desktop to phone.

Loop Now: a local multi-agent workspace for running your own team of agents, extensible with plugins | 本地运行的多 Agent 协作平台

An open-source cost controller for AI agent loops — stops a loop when it's actually converged and rolls back before it degrades, instead of

Your coding agent says "done". Orvant asks for proof. A skill for Claude Code, Codex and other file-capable agents, plus a Python engine tha

Use Codex, GLM, and other coding agents as Claude Code subagents.

Resource-aware multi-agent orchestration for Codex and DeepSeek Harness (All in Flash DSH plugin)

A desktop workspace (inspired by Grok Bot & Muse) for AI agents that collaborate, write code, and use tools. Run locally or on your own serv

Open Dynamic Workflows: TypeScript CLI runtime for Claude Code-style dynamic workflows across Codex, Claude Code, Gemini, Qwen, Kimi, and cu

A visual manager for fleets of Claude Code, Codex and Muse agents — real terminals, agents that message each other, teams that run tickets o

Production-Grade AI Agent Development Full-Chain Guide: Development, Testing, and Base Framework

Your local-first command center for working with AI agents like a real team.

The harness orchestrator — a local-first kanban for running Claude Code, Codex, and other CLI coding agents in parallel, each in its own git

"AI 桌面管家 · 多 Agent 协作编排 · 一句话调动团队完成复杂任务

A Rust-native, multi-agent development cockpit for macOS — spawn isolated worktrees, run CLI coding agents in parallel, and review every cha