777genius / agent-teams-ai

A kanban-style desktop app for orchestrating autonomous AI agent teams that collaborate, communicate, and review each other's work across 200+ LLM models

活跃维护 AGPL-3 TypeScript Tracked
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agent-teams claude claude-code ai-agents developer-tools electron llm typescript multi-agent codex openai opencode mcp-server agent-to-agent agent-orchestration coding-agent cursor github-copilot kiro multi-agent-systems

星标趋势

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AI 分析

项目摘要

Agent Teams AI is a free desktop application that lets users orchestrate teams of AI agents working autonomously on tasks via a kanban board interface. Agents communicate with each other, review each other's work, and handle tasks independently while the user provides high-level direction. It supports 200+ models across 75+ LLM providers including Claude Code, Codex, OpenCode, Cursor, and GitHub Copilot, with a free tier requiring no authentication.

为什么值得关注

The project stands out for its broad multi-provider LLM support, visual kanban-based agent management, and agent-to-agent collaboration features including peer code review. With 17 releases in 6 months, 26 contributors, and a free no-auth tier, it offers an accessible entry point for teams wanting to experiment with multi-agent orchestration without vendor lock-in.

优势

  • Extensive LLM provider support (200+ models, 75+ providers) with free no-auth tier
  • Visual kanban interface for intuitive multi-agent workflow management
  • Agent-to-agent communication and peer code review capabilities
  • Active development with 17 releases in 6 months and CI/CD pipeline
  • Desktop app built with Electron for cross-platform accessibility

局限性

  • No Docker support for containerized deployment
  • No examples directory to help new users get started quickly
  • Relatively new project (created Feb 2026) with limited track record
  • AGPL-3.0 license may restrict commercial adoption

使用场景

  • Orchestrating multiple AI coding agents for parallel software development
  • Managing AI-assisted project workflows with visual kanban tracking
  • Automated code review pipelines using multiple agents with different specialties
  • Prototyping and comparing outputs across multiple LLM providers simultaneously
目标用户: Software developers and engineering teams who want to orchestrate multiple AI coding agents through a visual interface without managing complex infrastructure
学习曲线:
分析模型:LongCat-2.0 | 分析时间:1 个月前