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Agent Teams AI Review

Agent Teams AI is an open-source desktop orchestrator that allows users to create teams of autonomous AI agents for collaborative task execution and project management.

shipped Sep 16, 2026codefree

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Why it matters

1Agent Teams AI is an open-source desktop orchestrator for managing AI coding agents.

2The platform includes a real-time Kanban board for task management and code review tools.

3It was open-sourced on August 31, 2026, under its former name Vicoa.

4Compliance includes a 30-day data retention policy after account deletion, with no training on user data.

About Agent Teams AI

Business Model

Freemium SaaS

Founded

2026

Funding

Bootstrapped

Platforms

macOS, Linux, Windows

Target Audience

Developers looking for collaborative AI tools

Pricing Plans

Free

• Free model with no auth for first runs
• Unlimited agent teams
• Kanban board with real-time updates
• Code review with diff view

GitHubOpen Source

Specs

API Docs

View Documentation →

GitHub

View Repository →

API Available

Yes, public API

Screenshots

overview

What is Agent Teams AI?

Agent Teams AI is an AI agent orchestration tool developed by 777genius that enables developers and project managers to create and manage teams of autonomous AI agents. It allows these agents to handle tasks, communicate with each other, and collaborate on projects, streamlining software development workflows. The platform, available at agentteams.live, is an open-source desktop application designed to coordinate AI coding agents, facilitating planning, delegation, execution, and review of tasks with human oversight. It was open-sourced on August 31, 2026, under its former name Vicoa, making the entire stack self-hostable across web, desktop (Mac, Windows, Linux), mobile (iOS, Android), backend, and CLI components. The tool's privacy policy, located at https://agentteams.com/privacy-policy, states that user data is retained for 30 days after account deletion, except where legally required, and user data is never used for training purposes.

features

Key Features of Agent Teams AI

Agent Teams AI provides a comprehensive set of features designed to facilitate autonomous AI agent collaboration and project management, with a focus on software development tasks. The platform includes tools for team creation, real-time task tracking, and integrated development functionalities.

Creation of agent teams with defined roles for specialized task execution.
Real-time Kanban board for visual task management, tracking progress, blockers, and handoffs.
Built-in code editor with Git support for direct code interaction and version control.
Token analytics and budget tracking to monitor and manage AI model usage costs.
Cross-team communication mechanisms for agents to interact and share information.
Tools for automated code review, including diff views for human oversight.
Agent Graph with force-directed visualization and Kanban task layout (introduced July 30, 2026, v1.2.0).
Per-team tool approval controls and task comment notifications (introduced July 30, 2026, v1.2.0).
MCP Connector for agents to utilize external tools by pasting an MCP server address (live July 4, 2026).
Controller APIs and Dashboard v1.2.4 for visible and controllable long-running project workflows (introduced August 22, 2026, v1.2.3).

use cases

Who Should Use Agent Teams AI?

Agent Teams AI is primarily designed for professionals involved in software development and project management who seek to leverage autonomous AI agents for increased productivity and collaborative problem-solving. Its features cater to specific roles and scenarios within the software development lifecycle.

Team Leads & Project Managers: For orchestrating highly autonomous AI agent teams, automating task breakdown, parallel execution, and work review, and resolving blockers with minimal human supervision.
Engineers & Developers: For full-stack feature development, codebase migration (e.g., JavaScript to TypeScript), dependency upgrades, and automated code review.
Researchers: For facilitating collaborative problem-solving among AI agents, allowing multiple agents to investigate different aspects of a problem and share findings.
Organizations requiring Automated Software Release Planning: To streamline the planning, execution, and review stages of software releases using AI agent teams.

how to use

How to Use Agent Teams AI

To begin using Agent Teams AI, users typically download the desktop application and configure their AI model providers. The platform then allows for the creation and management of agent teams to address specific project requirements.

1Download and install the Agent Teams AI desktop application for macOS, Linux, or Windows from agentteams.live.
2Configure AI model providers and settings within the application, ensuring clarity in provider and model setup (improved in v2.14.2, September 11, 2026).
3Create a new team of agents, assigning specific roles (e.g., Backend Dev, Frontend Dev, QA Engineer) to each agent.
4Provide high-level commands or project goals to the agent team, which will then break down tasks and initiate collaboration.
5Monitor agent progress and interactions on the real-time Kanban board and review code changes using the built-in diff view.
6Utilize features like the MCP Connector (live July 4, 2026) to integrate external tools for agents.

pricing

Agent Teams AI Pricing & Plans

Agent Teams AI operates on a freemium model, offering its core functionalities at no cost. The platform is open-source, allowing users to self-host the entire stack without licensing fees. While the application itself is free, users are responsible for the token costs associated with the AI models they integrate and utilize.

Free: $0 – Includes all core features for creating and managing autonomous AI agent teams, real-time Kanban board, code editor with Git support, and token analytics.

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Pros

+Open-source and self-hostable across multiple platforms (web, desktop, mobile, backend, CLI).
+Includes a real-time Kanban board for visual task tracking and project management.
+Features a built-in code editor with Git support and tools for automated code review.
+Facilitates collaborative problem-solving among AI agents with defined roles and communication.
+Offers token analytics and budget tracking to manage AI model usage costs.
+Actively developed with frequent updates, including new features like Agent Graph and Controller APIs.

Cons

−Potential for 'Cascade Error' where early agent mistakes can compound, requiring significant human oversight.
−Token costs for AI models can be substantial, potentially reaching $10-$60 per hour for coding agents.
−Setup and integration with existing organizational systems can be time-consuming.
−Requires specific use cases to justify the token expenditure and setup effort.
−Lacks a dedicated API for external programmatic control, relying on desktop application interaction.

Policies

Pricing Page

View Pricing→

Similar Tools

Agent Teams AI vs Competitors

Agent Teams AI distinguishes itself in the AI agent orchestration landscape through its open-source desktop orchestrator approach, integrated Kanban board, and dedicated code review tools, particularly for collaborative coding tasks.

SuperAGIOn Stork

Provides an open-source platform with a web UI for building, deploying, and managing autonomous AI agents and their workflows.

SuperAGI offers a more comprehensive platform for agent management and deployment with a UI, similar to Agent Teams AI. However, its built-in task management and code review features might not be as explicitly integrated or as polished as a dedicated kanban board.

AutoGenOn Stork

A flexible framework for building multi-agent conversation systems, enabling agents with different roles to communicate and collaborate to solve complex tasks.

AutoGen is a powerful Python library for defining and orchestrating agent teams, similar to the core agent collaboration of Agent Teams AI. The main trade-off is that AutoGen requires coding to set up and use, lacking the ready-made UI, kanban board, and integrated code review tools of Agent Teams AI, thus requiring a different workflow.

CrewAIOn Stork

A framework for orchestrating role-playing autonomous AI agents, allowing users to define agents with specific roles, tools, and goals for collaborative task execution.

CrewAI provides a robust Python framework for creating collaborative agent teams, similar to Agent Teams AI's core functionality. However, like AutoGen, it's a library and does not offer a pre-built UI, kanban board, or dedicated code review features, requiring more development effort and a code-centric workflow compared to Agent Teams AI.

OpenDevin↗

An open-source autonomous AI software engineer that can plan, execute, and review code, aiming to automate software development tasks.

OpenDevin focuses specifically on autonomous AI for software development, including code review capabilities, which aligns with one aspect of Agent Teams AI. While it involves agent collaboration for coding tasks, it is more specialized in software engineering and might not offer the general-purpose task management (like a kanban board) or broader agent team collaboration features found in Agent Teams AI.

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GitHubgithub.com/777genius/agent-teams-ai