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AI Agent Analysis
AA

777genius/agent-teams-ai

You're the boss, agents are your team. They handle tasks on their own, message each other, and review each other's work. You just watch the kanban board and give high-level commands. Codex/Claude/OpenCode/Cursor/Grok/GitHub Copilot/Kiro/Z.AI/MiniMax/Kimi(200+ models, 75+ LLM providers, free models no auth). Build your AI company with multiple teams

stars
1.7k
Language
TypeScript
GitHub
Source and compliance noteLast synced: Jul 28, 2026

Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.

Original GitHub sourceMethodologyEditorial Policy

Overview

Agent Teams AI is a free desktop application that lets you orchestrate multiple AI agents as a team, assigning them roles and tasks on a Kanban board. Its core value proposition is enabling a 'boss' to give high-level commands while agents autonomously handle tasks, communicate, and review each other's work, supporting over 200 models from 75+ providers.

Installation

Download the latest release from GitHub or visit agentteams.live; no signup or API key required to start with free models.

Problem solved

It solves the coordination overhead of managing multiple AI agents by providing a structured team framework with role assignment, autonomous task execution, and peer review, unlike single-agent tools or manual multi-agent setups. It also eliminates the need for API keys or signups for initial use, lowering the barrier to entry.

What you can build

Developers can build multi-agent coding workflows, project management pipelines, and automated review systems where agents act as team members with specific roles (e.g., coder, reviewer). Real-world use cases include autonomous code generation with built-in code review, multi-step project execution with agent-to-agent communication, and integrating diverse LLM providers in a single orchestrated environment. The ceiling includes creating entire AI-driven organizations with multiple teams, budget tracking, and complex task dependencies.

Community sentiment

Positive

No community feedback yet.

Concerns

No concerns documented yet.

Bottom line

This is ideal for developers and teams wanting to experiment with multi-agent orchestration without upfront costs or complex setup, especially for coding projects. It may not suit those needing production-grade reliability or extensive customization beyond the provided framework. The key trade-off is ease of use and flexibility versus potential complexity in managing many agents and providers.

Analyzed by Git-Stars - 7/27/2026