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/Kiro/Z.AI/Xiaomi/MiniMax/Kimi(300+ models, 200+ LLM providers, free models no auth) Build your AI company with multiple teams
No outside reports on file
Use this tool only with trusted AI models, keep API keys secure and limited, monitor what data agents are processing, and don't let it handle sensitive information without careful review.
Based on public adoption and transparency signals as of Oct 21, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesNo local folder access notedLOW
- Command executionNo shell command runner notedLOW
- Network reachConnects to outside service APINOTED
- CredentialsNo API token requiredLOW
- Package sourceGitHub (777genius/agent-teams-ai)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
No npm or PyPI package is listed. Install from source: github.com/777genius/agent-teams-ai ↗
About Agent Teams AI
This is a system for running multiple AI agents that work together as a team. The agents can talk to each other, complete tasks independently, and review each other's work while you watch a kanban board (a visual task tracker) and give top-level commands.
Who it’s for
Developers and teams who want to build AI-powered workflows where multiple agents collaborate automatically. It's designed for people experimenting with multi-agent systems using various AI models and providers.
Alternatives
- CrewAI: A simpler multi-agent framework with built-in task collaboration tools.
- Anthropic's multi-turn conversations: Use Claude or other models directly for sequential task logic without a separate agent coordinator.
- Autogen (Microsoft): An older multi-agent system with similar agent-to-agent communication patterns.
- LangChain agents: A flexible framework for building single and multi-agent systems with various LLM backends.
Setup
Check these steps against the project’s own instructions before running anything.
Follow the project's README at https://github.com/777genius/agent-teams-ai (opens external site) for installation and configuration instructions specific to your setup.
Why this grade
Signal-based grade (3/7 points): well starred on GitHub, public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- GitHub stars
- 2.4k
- Listing last refreshed
- 2026-10-29
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Security reports
No reports found for this package in our research (last checked 2026-10-30).
Risks to watch for
- Model provider accounts: The tool connects to 200+ LLM providers (like OpenAI, Claude, GitHub models). If an attacker tricks it, they could use your API keys to run expensive AI tasks or steal sensitive data you send to models.
- Agent autonomy: Agents make decisions on their own and communicate with each other. A compromised agent or malicious prompt could cause the team to perform unwanted actions or leak information between agents.
- Data in workflows: Tasks flowing through the kanban board and between agents may include sensitive information. If the system is misconfigured, this data could be exposed or logged insecurely.
- Untrusted task descriptions: The project description mentions "free models no auth," but instructions embedded in task prompts or agent definitions could hide malicious code or requests that bypass your intended controls.
- Dependency chain: This tool depends on many other packages for LLM provider integrations. Compromised dependencies could intercept API keys or modify agent behavior.
How to lower the risk
Least-privilege permissions
- Give agents only the specific permissions and API scopes they actually need.
- Use separate, limited API keys for each model provider if possible.
Network isolation
- Run agents in a sandbox or isolated network where they can't reach internal systems.
- Block agent outbound access except to approved LLM endpoints.
Monitoring
- Log all agent actions and inter-agent messages for audit trails.
- Alert on unusual task volumes, model costs, or data being sent to models.
Red flags to watch for
- Agents requesting access to systems or data they shouldn't need.
- Sudden spikes in API calls or tokens used (sign of a compromise).
- Agents sending sensitive data to unfamiliar model providers.
Questions
How do I install Agent Teams AI?
Agent Teams AI does not publish a standalone npm or PyPI package. Clone or follow the setup instructions in its source repository at github.com/777genius/agent-teams-ai.
Are there security reports about Agent Teams AI?
No reports found for this package in our research (last checked 2026-10-30). Agent Teams AI currently holds Grade C (Moderate risk signals) based on public adoption and transparency signals. Key risk areas to watch include model provider accounts, agent autonomy, data in workflows.
Is Agent Teams AI actively maintained?
Agent Teams AI has 2.4k GitHub stars. Our directory data was last refreshed on 2026-10-29. Check recent commit activity, release tags, and open issues at github.com/777genius/agent-teams-ai before pinning it in production.
What are alternatives to Agent Teams AI?
Notable alternatives to Agent Teams AI include CrewAI (A simpler multi-agent framework with built-in task collaboration tools), Anthropic's multi-turn conversations (Use Claude or other models directly for sequential task logic without a separate agent coordinator), Autogen (Microsoft) (An older multi-agent system with similar agent-to-agent communication patterns), LangChain agents (A flexible framework for building single and multi-agent systems with various LLM backends). You can also compare Agent Teams AI side by side with other MCP servers in the Related tools section on this page.
README badge and team notes
Maintain or use Agent Teams AI? Show its live grade in your GitHub README, docs site, or run a check from the terminal before you install.
GitHub README Markdown:
[](https://agentarmorhq.com/skills/777genius-agent-teams-ai)HTML embed:
<a href="https://agentarmorhq.com/skills/777genius-agent-teams-ai"><img src="https://agentarmorhq.com/api/badge/777genius-agent-teams-ai" alt="AgentArmorHQ Risk Grade for Agent Teams AI" height="20" /></a>Terminal check:
curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "777genius-agent-teams-ai"Share with your security lead
Need sign-off to use agent-teams-ai? Copy this note for Slack, a ticket or a pull request.
### AgentArmorHQ Security Review Memo: agent-teams-ai
- **Listing URL:** https://agentarmorhq.com/skills/777genius-agent-teams-ai
- **Type:** App connector
- **Risk Grade:** Grade C (Moderate risk signals)
- **Outside Security Advisories on File:** 0
- **Public Adoption:** 2.4k GitHub stars
#### Permission & Blast-Radius Signals
- **Local files:** No local folder access noted
- **Command execution:** No shell command runner noted
- **Network reach:** Connects to outside service API
- **Credentials:** No API token required
- **Package source:** GitHub (777genius/agent-teams-ai)
#### Recommended Hardened Setup
- **Source Repo:** https://github.com/777genius/agent-teams-ai
- **Controls:** Pin an exact version in `.mcp.json`, scope access to a single workspace folder, and use a least-privilege read-only token where supported.
_Based on public adoption and transparency signals as of Oct 21, 2026. Our opinion, not a code audit or security guarantee._Key facts
- Type
- App connector
- Publisher
- 777genius
- Source code
- github.com/777genius/agent-teams-ai
- Est. context load
- ~800 tokens / turn (~4 tool schemas, 0.4% of 200k context)
- Popularity
- 2.4k GitHub stars
- Last updated
- 2026-10-29
- Last graded
- 2026-10-21
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