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agt

Local-first multi-agent orchestration. Tell a lead agent a goal: it writes the prompts, creates the agents and MCP tools, and runs the work in a group chat.

Install / Use

claude mcp add blacsheep -- npx -y github:blacsheep/agt

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

83/100

Supported Platforms

Claude Code
Claude Desktop
OpenAI Codex

Our assessment of agt

agt scores 83/100 on our quality scale, 649th of 925 AI & Machine Learning skills we index.

Its MCP Server is 9.7 KB long, well organised into 12 sections with 4 code examples: a thorough specification that gives an agent plenty to work with.

It has 10 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
4/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so agt is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 97/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

agt compared with similar skills

All 4 of these similar skills score higher than agt; compare them before choosing.

SkillScoreStarsUpdatedFormat
agt (this skill)by blacsheep83101d agoMCP Server
Agent-Reachby Panniantong100105.5k3d agoCLAUDE.md
claude-memby thedotmack100104.0ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10088.7k2d agoCLAUDE.md
headroomby headroomlabs-ai10078.1ktodayCLAUDE.md

Frequently asked questions

How do I install agt?
Run claude mcp add blacsheep -- npx -y github:blacsheep/agt. The install tabs above show the steps for each supported agent.
Which AI agents does agt work with?
It is written for Claude Code, Claude Desktop and OpenAI Codex, as a MCP Server file. Other agents that read the same format can often use it too.
Is agt safe to use?
It is MIT-licensed and scores 97/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is agt still maintained?
The repository was last updated yesterday, so agt is actively maintained.
<p align="center"> <img src="docs/public/favicon.svg" width="72" height="72" alt="agt"> </p> <h1 align="center">agt</h1> <p align="center"> <b>Agents that build their own team.</b><br> English · <a href="README.zh-CN.md">简体中文</a> · <a href="https://blacsheep.github.io/agt/">Documentation</a> </p> <p align="center"> <a href="https://github.com/blacsheep/agt/actions/workflows/ci.yml"><img src="https://github.com/blacsheep/agt/actions/workflows/ci.yml/badge.svg?branch=main" alt="CI"></a> <a href="https://github.com/blacsheep/agt/releases/latest"><img src="https://img.shields.io/github/v/release/blacsheep/agt" alt="Release"></a> <a href="LICENSE"><img src="https://img.shields.io/github/license/blacsheep/agt" alt="License: MIT"></a> <img src="https://img.shields.io/badge/platform-Linux%20%7C%20macOS%20%7C%20Windows-lightgrey" alt="Linux | macOS | Windows"> <a href="https://blacsheep.github.io/agt/"><img src="https://img.shields.io/badge/docs-online-blue" alt="Documentation"></a> </p>

agt is a multi-agent orchestration framework that runs on your own machine. You talk to one agent, the lead.

Tell it what you want done, and it writes the role prompts, creates the agents, has a coding agent build any tool that is missing, puts everyone in a group chat and runs the work. You watch, step in when you want to, and approve what needs approving.

Sped-up recording: one message to the lead, a three-person research team created, two rounds of debate and a conclusion, with no one stepping in

What is different about it

In most multi-agent frameworks you define the agents, their tools and how they connect before anything runs. In agt, setting up the team is work the agents do themselves.

Agents manage resources with tools. Prompts, models, MCP servers and agent definitions are files that agt manages, and an agent given the resource_management capability can create and change them through tool calls. That is how the lead gets from one sentence to a working team, and everything it creates is a file you can read and edit.

Teams work in chats. Agents have direct and group chats and @mention each other, the same way people do. A scheduler decides who replies, who waits and who stays quiet. There is no workflow graph to design: orchestration happens in the conversation, which takes whatever shape the work needs.

Isolation is enforced by tools. An agent can only do what its attached tools allow, and a new agent does not inherit the tools of the agent that created it. In the murder mystery below, each player's tool can only ever return that player's own clue. No prompt has to ask anyone not to look.

Existing coding agents join the team. An agent can run on Codex, Claude Code, DeepSeek Harness (dsh) or another ACP agent instead of the built-in model loop. It keeps its own tools and sandbox, and works with the rest of the team through agt's messaging, tasks and memory. The lead can hand one a spec, get back a tested MCP server, and attach that server to the agents that need it.

Work survives restarts. Conversations, runs, tasks and approvals are stored in SQLite. Pending work picks up where it stopped, and work whose outcome is unclear is flagged for you instead of being run twice.

You keep control. Every tool call can wait for you, go to a reviewer model first, or run freely. The Web console shows who is working on what, including chats between agents that you are not part of.

See it work

A complete project and two real runs, each started by a single message to the lead. The examples page walks through all three.

AI Werewolf, a full project on agt. Twelve AI players and an AI God play a 12-seat Werewolf game. Each player has an engine MCP server of its own, which keeps the roles apart. One message to the lead runs a whole game; voice and replay agents then turn it into audio, a web replay and a video.

God's-view replay of an AI Werewolf game

A murder mystery with a tool built by Codex. The lead had a Codex agent write a clue server, then created a game master and three players, gave each player a copy of the server locked to that player, and ran the game.

Sped-up recording: Codex writes the clue server, each role gets its own locked instance, and the game plays through to the reveal

A research team that argues. Asked whether to migrate to Postgres 17, the lead created a performance researcher, an operations researcher and a reviewer, and opened a group chat. The reviewer challenged both researchers, and after two rounds the group reached a verdict. The recording at the top of this page is this run.

Install

agt comes as a command-line tool and as a desktop app. Both use the same data, so you can switch between them.

Command line

macOS and Linux:

curl --proto '=https' --tlsv1.2 -LsSf https://github.com/blacsheep/agt/releases/latest/download/agt-cli-installer.sh | sh

Windows (PowerShell):

powershell -ExecutionPolicy Bypass -c "irm https://github.com/blacsheep/agt/releases/latest/download/agt-cli-installer.ps1 | iex"

The installer puts a prebuilt agt in ~/.local/bin; the Web console is built into it. Other ways to install, updating and uninstalling are in Installation.

Desktop app

AGT Studio is the console as an app for macOS, Windows and Linux, with a tray icon and notifications. Download the installer for your system (.dmg, -setup.exe, .AppImage or .deb) from the latest release. See Desktop app.

Either way, you need a model API that supports tool calls: OpenAI or a compatible service, Anthropic, or Google Gemini. Coding agents also need the tool they run on, such as the Codex CLI, Claude Code or DeepSeek Harness.

Quick start

agt web

Open the link it prints, including the token after #, or open AGT Studio. Connect a model, create the lead, and send it a goal; the Quick start takes you through each step. The console only listens on 127.0.0.1. To reach it on a server, use an SSH tunnel.

Documentation

The documentation site is in English and Chinese.

| If you want to | Read | | --- | --- | | Understand the idea | What is agt? | | Get a lead building a team | Quick start | | See two full runs | Examples | | Learn the moving parts | Core concepts | | Set up models, agents, MCP, coding agents, tasks, memory or approvals | Guides | | Look up a command or setting | Modules | | Fix an agent that does not reply | Troubleshooting | | Know what is safe to expose | Security model |

Where your data lives

Everything is kept in one directory, ~/.agt, created the first time you run agt. Set AGT_HOME to keep it somewhere else, or run agt init <dir> to start a separate home for a project:

~/.agt/
  config.yaml                       workspace settings
  providers/ models/ prompts/ skills/ mcps/ agents/ harnesses/
  im/im.db                          conversations and messages
  runtime/runtime.db                runs, tasks, approvals, harness sessions

agt is meant for one person on a trusted machine. It is not a hosted or multi-user service.

Status and where it could go

agt is a first implementation of an idea: agents that build their own team and work together in chats. It is early, and it likely has bugs as well as design decisions that did not get enough thought.

If the ideas are useful to you, fork it and adapt it to your own needs. Some directions we have thought of:

  • One lead for many projects. Each harness has its own working directory, so Codex, Claude Code and DeepSeek Harness sessions in different project directories can all join, each looking after its own project while you talk to a single lead. Some existing projects already manage sessions better; you are welcome to start from an idea like agt's and build something better.
  • A base for multi-agent setups that need isolation. Each agent sees only the conversations it is in and the tools attached to it, which suits games where players hold different information, such as Werewolf or a murder mystery. AI Werewolf is built this way.
  • Simulations in the style of an AI town. Keep each character apart with agt, and put an interaction layer between them that decides who meets whom, when, and what they hear, then sends the messages to the right agents. Each character keeps its own memory and acts on its own, and the interaction layer drives how the world unfolds.

Issues and pull requests are welcome too.

Contributing

Build and test instructions, the crate layout and the release process are in CONTRIBUTING.md. The internal design is documented in Architecture (Chinese).

Acknowledgements

Thanks to the LINUX DO community for its support and discussions.

Citation and license

If you use agt in research, cite it with CITATION.cff. agt is released under the MIT License.

Related Skills

View on GitHub
GitHub Stars10
CategoryAI
Updated1d ago
Forks1

Languages

Rust

Trust signals

97/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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