Multi-agent team operating system for Claude Code. 108 MCP tools, 40+ agent templates, 10 lifecycle hooks, 7 pipeline workflows. Persistent teams, structured meetings, task wall, real-time React dashboard. No LangChain/AutoGen — pure CC native integration.

AI Team OS

Your AI coding tool stops when you stop prompting. Ours doesn’t.

AI Team OS turns Claude Code into a self-driving AI company. You’re the Chairman. AI is the CEO. Set the vision — the system executes, learns, and evolves autonomously.

The Problem With Every Other AI Tool

Every AI coding assistant works the same way: you prompt, it responds, it stops. The moment you step away, work stops. You come back to a blank prompt.

AI Team OS works differently.

You walk away at night. The next morning you open your laptop and find:

The CEO checked the task wall, picked up the next highest-priority item, and shipped it
When it hit a blocker that needed your approval, it parked that thread and switched to a parallel workstream
R&D agents scanned three competitor frameworks and found a technique worth adopting
A brainstorming meeting was organized, 5 agents debated 4 proposals, and the best one was put on the task wall

You didn’t prompt any of that. The system just ran.

How It Works

You’re the Chairman. The AI Leader is the CEO.

The CEO doesn’t wait for instructions. It checks the task wall, picks the highest-priority item, assigns the right specialist Agent, and drives execution. When blocked, it switches workstreams. When all planned work is done, R&D agents activate — scanning for new technologies, organizing brainstorming meetings, and feeding improvements back into the system.

Every failure makes the system smarter. “Failure Alchemy” extracts defensive rules, generates training cases for future Agents, and submits improvement proposals — the system develops antibodies against its own mistakes.

Core Capabilities

1. Autonomous Operation

The CEO never idles. It continuously advances work based on task wall priorities:

Checks the task wall for next highest-priority item when a task completes
When blocked on something requiring your approval, parks that thread and switches to parallel workstreams
Batches all strategic questions and reports them when you return — no interruptions for tactical decisions
Deadlock detection: if the loop stalls, it surfaces the blocker rather than spinning

2. Self-Improvement

The system doesn’t just execute — it evolves:

R&D cycle: Research agents scan competitors, new frameworks, and community tools. Findings go to brainstorming meetings where agents challenge each other. Conclusions become implementation plans on the task wall.
Failure Alchemy: Every failed task triggers root cause extraction, classification, and three outputs:
- Antibody — failure stored in team memory to prevent the same mistake
- Vaccine — high-frequency failure patterns converted into pre-task warnings
- Catalyst — analysis injected into Agent system prompts to improve future execution

3. Team Collaboration

Not a single Agent. A structured organization:

25 professional Agent templates (23 base + 2 debate roles) with recommendation engine — Engineering, Testing, Research, Management — ready out of the box
8 structured meeting templates with keyword-based auto-select, built on Six Thinking Hats, DACI, and Design Sprint methodologies
Department grouping — Engineering / QA / Research with cross-team coordination
Every meeting produces actionable conclusions. “We discussed but didn’t decide” is not an outcome.

4. Full Transparency

Nothing is a black box:

Decision Cockpit: event stream + decision timeline + intent inspection — every decision has a traceable record
Activity Tracking: real-time status of every Agent and what it’s working on
What-If Analyzer: compare multiple approaches before committing, with path simulation and recommendations

5. Workflow Pipeline Orchestration

Every task follows a structured, enforced workflow — no more ad-hoc execution:

7 pipeline templates: feature (Research→Design→Implement→Review→Test→Deploy), bugfix, research, refactor, quick-fix, spike, hotfix
Auto-attach via task_type: pass task_type="feature" to task_create and the pipeline mounts automatically
Progressive enforcement: hook detects tasks without pipelines — soft reminder → strong reminder → hard block (exit 2) on third occurrence
Auto phase progression: each stage recommends the right Agent template; pipeline_advance moves to next stage automatically
Lightest escape hatch: quick-fix (Implement→Test only) for truly trivial changes
Channel communication: team: / project: / global channels with @mention support
Debate mode: 4-round structured debate (Advocate→Critic→Response→Judge) via debate_start / debate_code_review
Git automation: git_auto_commit / git_create_pr / git_status_check for streamlined version control
Semantic cache: BM25 + Jaccard similarity matching with JSON persistence and TTL expiry
Execution pattern memory: success/failure pattern recording + BM25 retrieval + subagent context injection

6. Safety & Behavioral Enforcement

Built-in guardrails so the system can run unsupervised without surprises:

Guardrails L1: 7 dangerous pattern detections + PII warnings + InputGuardrailMiddleware
Local agent blocking: all non-readonly agents must declare team_name/name — prevents rogue background agents
S1 safety rules: regex-based scan catches destructive commands (rm -rf, force push, hardcoded secrets) including uppercase flags and heredoc patterns
4-layer defense rule system: 48+ rules covering workflow, delegation, session, and safety layers
File lock / workspace isolation: acquire/release/check/list + TTL=300s + hook warnings to prevent concurrent edits
Agent trust scoring: trust_score (0-1) auto-adjusts on task success/failure, weighted into auto_assign
Agent Watchdog heartbeat: agent_heartbeat / watchdog_check with 5-min TTL — detects stalled or crashed agents automatically
SRE error budget model: GREEN/YELLOW/ORANGE/RED 4-level response with sliding window (20 tasks), error_budget_status / error_budget_update tools
Completion verification: verify_completion checks task status + memo existence — prevents hallucinated “done” reports
Ecosystem integration recipes: 4 preset recipes (GitHub / Slack / Linear / Full-stack team) via ecosystem_recipes() tool
find_skill 3-layer progressive discovery: quick recommend → category browse → full detail, reducing tool-call overhead

7. Zero Extra Cost

Runs entirely within your existing Claude Code subscription:

No external API calls, no extra token spend
MCP tools, hooks, and Agent templates are all local
100% utilization of your CC plan

8. Ecosystem Research Platform (progressive funnel in v1.5.0)

A project-isolated knowledge base that accumulates research findings over time. Each repo progresses through 4 stages, with token-efficient triggers and append-only history:

Stage 0 — Auto shallow-summary on archive: newly-archived repos automatically get a 200-400 char ai-engineer summary (core function / positioning / advantages). 8-class failure handling with self-learning (3+ same-class fails → pattern_record, future agents read lessons via pattern_search). Worker auto-revives deleted/private repos when GitHub returns 200 again.
Stage 1 — On-demand architecture analysis: user picks research direction (“memory_system”) → batch-dispatch backend-architect agents to read architecture key files
Stage 2 — Multi-perspective debate: triggers existing debate_start (NOT a built-in debate engine — reuses meeting system). Meeting → ecosystem reverse-writeback hook reminds Leader to record verdicts back to deep_review
Stage 3 — Reference / Integrate marking: mark_as_reference adds tag for future quick recall (avoid re-deep-scanning); start_integration triggers existing task_create for actual implementation
Project-customizable thresholds: each project sets min_stars / top_n / refresh_interval_days / focus_topics. AI Team OS default: stars ≥ 5K, top 200, focus on claude-code / mcp / agent-framework
Active vs Full dual-view: data is append-only forever. Stars-falling repos kept (just is_active=False); stars climbing back auto-promotes + re-queues Stage 0
Dashboard /ecosystem: list with stage badges + research timeline + candidate-filter page (/ecosystem/research) + per-project settings tab
30+ MCP tools / 15+ REST endpoints / SQLite append-only history snapshots

It Built Itself

AI Team OS managed its own development:

Organized 5 innovation brainstorming meetings with multi-agent debate
Conducted competitive analysis across CrewAI, AutoGen, LangGraph, and Devin
Shipped 67 tasks across 5 major innovation features
Generated 14 design documents totaling 10,000+ lines

The system that builds your projects… built itself.

How It Compares

Dimension	AI Team OS	CrewAI	AutoGen	LangGraph	Devin
Category	CC Enhancement OS	Standalone Framework	Standalone Framework	Workflow Engine	Standalone AI Engineer
Integration	MCP Protocol into CC	Independent Python	Independent Python	Independent Python	SaaS Product
Autonomous Operation	Continuous loop, never idles	Task-by-task	Task-by-task	Workflow-driven	Limited
Meeting System	8 structured templates with auto-select	None	Limited	None	None
Failure Learning	Failure Alchemy (Antibody/Vaccine/Catalyst)	None	None	None	Limited
Decision Transparency	Decision Cockpit + Timeline	None	Limited	Limited	Black box
Workflow Orchestration	7 pipeline templates + progressive enforcement	None	None	Manual	None
Rule System	4-layer defense (48+ rules) + behavioral enforcement	Limited	Limited	None	Limited
Agent Templates	25 ready-to-use + recommendation engine	Built-in roles	Built-in roles	None	None
Dashboard	React 19 visualization	Commercial tier	None	None	Yes
Open Source	MIT	Apache 2.0	MIT	MIT	No
Claude Code Native	Yes, deep integration	No	No	No	No
Extra Cost	$0 (CC subscription only)	API costs	API costs	API costs	$500+/mo

Architecture

┌─────────────────────────────────────────────────────────────────┐
│                     User (Chairman)                              │
│                         │                                       │
│                         ▼                                       │
│                   Leader (CEO)                                   │
│            ┌────────────┼────────────┐                          │
│            ▼            ▼            ▼                          │
│       Agent Templates  Task Wall  Meeting System                 │
│      (25 roles)       Loop Engine  (8 templates)                 │
│            │            │            │                          │
│            └────────────┼────────────┘                          │
│                         ▼                                       │
│              ┌──────────────────────┐                           │
│              │   OS Enhancement Layer│                           │
│              │  ┌──────────────┐    │                           │
│              │  │  MCP Server  │    │                           │
│              │  │ (107 tools)  │    │                           │
│              │  └──────┬───────┘    │                           │
│              │         │            │                           │
│              │  ┌──────▼───────┐    │                           │
│              │  │  FastAPI     │    │                           │
│              │  │  REST API    │    │                           │
│              │  └──────┬───────┘    │                           │
│              │         │            │                           │
│              │  ┌──────▼───────┐    │                           │
│              │  │  Dashboard   │    │                           │
│              │  │ (React 19)   │    │                           │
│              │  └──────────────┘    │                           │
│              └──────────────────────┘                           │
│                         │                                       │
│              ┌──────────▼──────────┐                            │
│              │  Storage (SQLite)   │                            │
│              │  + Alembic Migration│                            │
│              │  + Memory System    │                            │
│              └─────────────────────┘                            │
└─────────────────────────────────────────────────────────────────┘

Five-Layer Technical Architecture

Layer 5: Web Dashboard    — React 19 + TypeScript + Shadcn UI (18 pages)
Layer 4: CLI + REST API   — Typer + FastAPI
Layer 3: Team Orchestrator — LangGraph StateGraph
Layer 2: Memory Manager   — Mem0 / File fallback
Layer 1: Storage          — SQLite (development) / PostgreSQL (production) + Alembic migrations

Hook System (9 Lifecycle Events — The Bridge Between CC and OS)

SessionStart     → session_bootstrap.py          — Inject Leader briefing + 5 core rules + team state
SessionEnd       → send_event.py                 — Record session end event
SubagentStart    → inject_subagent_context.py    — Inject sub-Agent OS rules (2-Action etc.)
SubagentStop     → send_event.py                 — Record sub-Agent lifecycle event
PreToolUse       → workflow_reminder.py          — Workflow reminders + safety guardrails
PostToolUse      → send_event.py                 — Forward events to OS API
UserPromptSubmit → context_monitor.py            — Monitor context usage rate
Stop             → send_event.py                 — Record stop event
PreCompact       → pre_compact_save.py           — Auto-save progress before context compression

Quick Install (AI-Assisted)

Tell Claude Code:

“Read https://github.com/CronusL-1141/AI-company/blob/master/INSTALL.md and follow the instructions to install AI Team OS”

Claude Code will read the install guide and walk you through the setup automatically.

Important: Install AI Team OS to your system Python, not inside a project virtual environment. If installed in a venv, AI Team OS will only work in that specific project. Run deactivate first if a venv is currently active, then install.

Quick Start

Prerequisites

Python >= 3.11
uv (pip install uv)
Claude Code (MCP support required)
Node.js >= 20 (Dashboard frontend, optional)

Option A: Plugin Install (Recommended)

# Install uv (Python package runner, required for MCP server)
pip install uv

# Add marketplace + install plugin
claude plugin marketplace add CronusL-1141/AI-company
claude plugin install ai-team-os

# Restart Claude Code — first launch takes ~30s to set up dependencies
# Subsequent launches are instant

# Update to latest version anytime
claude plugin update ai-team-os@ai-team-os

Note: First launch after install takes ~30 seconds while dependencies are automatically configured. This only happens once — subsequent sessions start instantly with 107 MCP tools ready.

Option B: Manual Install

# Step 1: Clone the repository
git clone https://github.com/CronusL-1141/AI-company.git
cd AI-company

# Step 2: Run the installer (auto-configures MCP + Hooks + Agent templates + API)
python install.py

# Step 3: Restart Claude Code — everything activates automatically
# API server starts automatically when MCP loads. No manual startup needed.
# Verify: run /mcp in CC and check that ai-team-os tools are mounted

Option C: PyPI Install

pip install ai-team-os
python -m aiteam.scripts.install
# Restart Claude Code — tools activate automatically

Verify Installation

# Check OS health (API must be running — port may vary, check api_port.txt)
curl http://localhost:8000/api/health
# Expected: {"status": "ok"}

# Create your first team via CC
# Type in Claude Code:
# "Create a web development team with a frontend dev, backend dev, and QA engineer"

Uninstall

# Plugin install:
claude plugin uninstall ai-team-os
# Then manually remove residual data:
# Windows: rmdir /s %USERPROFILE%\.claude\plugins\data\ai-team-os-ai-team-os
# Unix:    rm -rf ~/.claude/plugins/data/ai-team-os-*
# Restart Claude Code to stop active hooks.

# Manual install:
python scripts/uninstall.py        # full cleanup
python scripts/uninstall.py --dry-run  # preview first

Start the Dashboard (optional)

cd dashboard
npm install
npm run dev
# Visit http://localhost:5173

Dashboard Screenshots

Command Center

Team Working — Live Activity Tracking

Team Working

Task Board — 68 Tasks Completed

Task Board

Meeting Room

Activity Analytics

Analytics

Event Log

Events

Auto-Wake System — Autonomous Task Advancement

Auto-Wake Demo

Auto-Wake System

The Leader supports scheduled auto-wake to autonomously advance tasks without supervision:

Automatically checks context usage and pending tasks every 10 minutes
When tasks are available, autonomously creates teams and assigns work
When user decisions are needed, records them asynchronously via the Briefing system
When context exceeds 80%, auto-saves progress and prompts to open a new session

Ecosystem Integration Recipes

AI Team OS is designed as a meta-plugin — it orchestrates other MCP servers rather than reimplementing their capabilities. Pre-built recipes let you integrate popular tools in minutes:

Recipe	Integrates With	What You Get
GitHub	`@modelcontextprotocol/github`	Auto PR creation, issue tracking, code review coordination
Slack	`@anthropics/slack-mcp`	Team notifications, decision escalation, status broadcasts
Linear	`linear-mcp-server`	Task sync, sprint tracking, bug triage automation
Full-Stack Team	GitHub + Slack + Linear	Complete development workflow with cross-tool orchestration

Use the ecosystem_recipes MCP tool to discover recipes, or see the full guide: docs/ecosystem-recipes.md

CC-First Design Principles

AI Team OS is built specifically for Claude Code, not as a standalone framework:

MCP Protocol native: All 107 tools are registered via MCP — no custom client, no API wrapper
Hook-driven lifecycle: 9 CC lifecycle events (SessionStart → PreCompact) provide deep integration without modifying CC internals
Agent templates as .md files: Installed to ~/.claude/agents/ (global) or .claude/agents/ (project-level) — CC’s native agent system, not a custom abstraction
Zero external dependencies at runtime: No external API calls, no cloud services — runs entirely within your CC subscription
Context-aware: Session bootstrap injects only 5 core rules (down from 23) to minimize context budget impact, with subagent context capped at 60 lines

MCP Tools

Expand to see all 107 MCP tools (22 modules)

Team Management

Tool	Description
`team_create`	Create an AI Agent team; supports coordinate/broadcast modes
`team_status`	Get team details and member status
`team_list`	List all teams
`team_briefing`	Get a full team panorama in one call (members + events + meetings + todos)
`team_setup_guide`	Recommend team role configuration based on project type

Agent Management

Tool	Description
`agent_register`	Register a new Agent to a team
`agent_update_status`	Update Agent status (idle/busy/error)
`agent_list`	List team members
`agent_template_list`	Get available Agent template list
`agent_template_recommend`	Recommend the best Agent template based on task description

Task Management

Tool	Description
`task_run`	Execute a task with full execution recording
`task_decompose`	Break a complex task into subtasks
`task_status`	Query task execution status
`taskwall_view`	View the task wall (all pending + in-progress + completed)
`task_create`	Create a new task (supports `auto_start` and `task_type` pipeline parameters)
`task_update`	Partial update of task fields with auto timestamps
`task_auto_match`	Intelligently match the best Agent based on task characteristics
`task_memo_add`	Add an execution memo to a task
`task_memo_read`	Read task history memos
`task_list_project`	List all tasks under a project

Pipeline Orchestration

Tool	Description
`pipeline_create`	Attach a workflow pipeline to a task (7 templates: feature/bugfix/research/refactor/quick-fix/spike/hotfix)
`pipeline_advance`	Advance pipeline to next stage; returns next-stage Agent template recommendation

Loop Engine

Tool	Description
`loop_start`	Start the auto-advance loop
`loop_status`	View loop status
`loop_next_task`	Get the next pending task
`loop_advance`	Advance the loop to the next stage
`loop_pause`	Pause the loop
`loop_resume`	Resume the loop
`loop_review`	Generate a loop review report (with failure analysis)

Meeting System

Tool	Description
`meeting_create`	Create a structured meeting (8 templates, keyword auto-select)
`meeting_send_message`	Send a meeting message
`meeting_read_messages`	Read meeting records
`meeting_conclude`	Summarize meeting conclusions
`meeting_template_list`	Get available meeting template list
`meeting_list`	List all meetings
`meeting_update`	Update meeting metadata

Channel Communication

Tool	Description
`channel_send`	Send a message to a channel (team:/project:/global) with @mention support
`channel_read`	Read messages from a channel
`channel_mentions`	Get unread @mentions for an agent

File Lock & Workspace Isolation

Tool	Description
`file_lock_acquire`	Acquire a file lock (TTL=300s) to prevent concurrent edits
`file_lock_release`	Release a file lock
`file_lock_check`	Check if a file is locked and by whom
`file_lock_list`	List all active file locks

Git Automation

Tool	Description
`git_auto_commit`	Auto-commit staged changes with generated message
`git_create_pr`	Create a pull request from current branch
`git_status_check`	Check git repository status

Debate System

Tool	Description
`debate_start`	Start a structured 4-round debate (Advocate→Critic→Response→Judge)
`debate_code_review`	Start a code review debate session

Guardrails

Tool	Description
`guardrail_check`	Run guardrail checks on a command string
`guardrail_check_payload`	Run guardrail checks on a structured payload

Execution Patterns

Tool	Description
`pattern_record`	Record a success/failure execution pattern
`pattern_search`	Search execution patterns via BM25 for context injection

Intelligence & Analysis

Tool	Description
`failure_analysis`	Failure Alchemy — analyze root causes, generate antibody/vaccine/catalyst
`what_if_analysis`	What-If Analyzer — multi-option comparison and recommendation
`decision_log`	Log a decision to the cockpit timeline
`context_resolve`	Resolve current context and retrieve relevant background information

Memory System

Tool	Description
`memory_search`	Full-text search of the team memory store
`team_knowledge`	Get a team knowledge summary

Trust & Reliability

Tool	Description
`agent_trust_scores`	View trust scores for all agents
`agent_trust_update`	Manually adjust an agent’s trust score
`agent_heartbeat`	Send a heartbeat signal from a running agent
`watchdog_check`	Check for stalled agents (5-min TTL timeout)
`error_budget_status`	View SRE error budget (GREEN/YELLOW/ORANGE/RED)
`error_budget_update`	Record task outcome against the error budget
`verify_completion`	Verify task completion (status + memo check, anti-hallucination)

Analytics

Tool	Description
`task_execution_trace`	Get unified execution timeline for a task
`task_replay`	Replay task execution history
`task_compare`	Compare two task executions side-by-side
`diagnose_task_failure`	Auto-diagnose why a task failed

Briefing System

Tool	Description
`briefing_add`	Add a decision item for user review
`briefing_list`	List pending briefing items
`briefing_resolve`	Resolve a briefing item with a decision
`briefing_dismiss`	Dismiss a briefing item

Reports (Database-backed)

Tool	Description
`report_save`	Save a report to database with project isolation (research/design/analysis/meeting-minutes)
`report_list`	List reports with filtering by project, type, author, topic
`report_read`	Read a report by ID

Scheduler

Tool	Description
`scheduler_create`	Create a scheduled periodic task
`scheduler_list`	List scheduled tasks
`scheduler_delete`	Delete a scheduled task
`scheduler_pause`	Pause a scheduled task

Cache Management

Tool	Description
`cache_stats`	View semantic cache hit/miss statistics
`cache_clear`	Clear the semantic cache

Ecosystem

Tool	Description
`ecosystem_recipes`	Discover integration recipes (GitHub/Slack/Linear/Full-stack)
`send_notification`	Send notifications via Slack/webhook
`cross_project_send`	Send cross-project messages
`cross_project_inbox`	Read cross-project inbox

Prompt Registry

Tool	Description
`prompt_version_list`	List agent template versions
`prompt_effectiveness`	View template effectiveness metrics

Project Management

Tool	Description
`project_create`	Create a project
`project_list`	List all projects
`project_update`	Update project settings
`project_delete`	Delete a project
`project_summary`	Get a quick project status summary
`phase_create`	Create a project phase
`phase_list`	List project phases

System Operations

Tool	Description
`os_health_check`	OS health check
`event_list`	View the system event stream
`os_report_issue`	Report an issue
`os_resolve_issue`	Mark an issue as resolved
`agent_activity_query`	Query agent activity history and statistics
`find_skill`	3-layer progressive skill discovery (quick recommend / category browse / full detail)
`team_close`	Close a team and cascade-close its active meetings
`team_delete`	Delete a team

Agent Template Library

25 ready-to-use professional Agent templates with recommendation engine, covering a complete software engineering team. Templates are installed to plugin/agents/ (project-level) and ~/.claude/agents/ (global, available across all projects).

Engineering (13 templates)

Template	Role	Use Case
`engineering-software-architect`	Software Architect	System design, architecture review
`engineering-backend-architect`	Backend Architect	API design, service architecture
`engineering-frontend-developer`	Frontend Developer	UI implementation, interaction development
`engineering-ai-engineer`	AI Engineer	Model integration, LLM applications
`engineering-mcp-builder`	MCP Builder	MCP tool development
`engineering-code-reviewer`	Code Reviewer	Code quality review, PR review
`engineering-database-optimizer`	Database Optimizer	Query optimization, schema design
`engineering-devops-automator`	DevOps Automation Engineer	CI/CD, infrastructure
`engineering-sre`	Site Reliability Engineer	Observability, incident response
`engineering-security-engineer`	Security Engineer	Security review, vulnerability analysis
`engineering-rapid-prototyper`	Rapid Prototyper	MVP validation, fast iteration
`engineering-mobile-developer`	Mobile Developer	iOS/Android development
`engineering-git-workflow-master`	Git Workflow Master	Branch strategy, code collaboration

Testing (4 templates)

Template	Role	Use Case
`testing-qa-engineer`	QA Engineer	Test strategy, quality assurance
`testing-api-tester`	API Test Specialist	Interface testing, contract testing
`testing-bug-fixer`	Bug Fix Specialist	Defect analysis, root cause investigation
`testing-performance-benchmarker`	Performance Benchmarker	Performance analysis, load testing

Research & Support (3 templates)

Template	Role	Use Case
`specialized-workflow-architect`	Workflow Architect	Process design, automation orchestration
`support-technical-writer`	Technical Writer	API docs, user guides
`support-meeting-facilitator`	Meeting Facilitator	Structured discussion, decision facilitation

Management (2 templates)

Template	Role	Use Case
`management-tech-lead`	Tech Lead	Technical decisions, team coordination
`management-project-manager`	Project Manager	Schedule management, risk tracking

Debate Roles (2 templates)

Template	Role	Use Case
`debate-advocate`	Debate Advocate	Propose and defend solutions in structured debates
`debate-critic`	Debate Critic	Challenge proposals and find weaknesses

Utility (1 template)

Template	Role	Use Case
`team-member`	Generic Team Member	Default role for general-purpose tasks

Roadmap

Completed

In Progress / Planned

Multi-tenant isolation
Production validation and performance optimization
Claude Code Plugin Marketplace listing
Full integration test suite
Documentation site (Docusaurus)
Video tutorial series

Project Structure

ai-team-os/
├── src/aiteam/
│   ├── api/           — FastAPI REST endpoints
│   ├── mcp/
│   │   ├── server.py  — MCP server entry point
│   │   └── tools/     — 22 tool modules (107 tools total)
│   │       ├── agent.py, analytics.py, briefing.py, cache.py,
│   │       ├── channels.py, error_budget_tool.py, file_lock.py,
│   │       ├── git_ops.py, guardrails.py, infra.py, loop.py,
│   │       ├── meeting.py, memory.py, pipeline.py, project.py,
│   │       ├── reports.py, scheduler.py, task.py, task_analysis.py,
│   │       ├── team.py, trust.py, watchdog.py
│   │       └── __init__.py  — Tool tier definitions (CORE 15 / ADVANCED)
│   ├── loop/          — Loop Engine
│   ├── meeting/       — Meeting system
│   ├── memory/        — Team memory
│   ├── orchestrator/  — Team orchestrator
│   ├── storage/       — Storage layer (SQLite/PostgreSQL) + Alembic migrations
│   ├── templates/     — Agent template base classes
│   ├── hooks/         — CC Hook scripts (9 lifecycle events)
│   └── types.py       — Shared type definitions
├── plugin/
│   ├── agents/        — 25 Agent templates (.md)
│   └── .claude-plugin/ — Plugin manifest
├── dashboard/         — React 19 frontend (18 pages)
├── docs/              — Design documents + ecosystem recipes
├── tests/             — Test suite (631+ tests)
├── install.py         — One-click install script
└── pyproject.toml

Contributing

Contributions are welcome! We especially appreciate:

New Agent templates: If you have prompt designs for specialized roles, PRs are welcome
Meeting template extensions: New structured discussion patterns
Bug fixes: Open an Issue or submit a PR directly
Documentation improvements: Found a discrepancy between docs and code? Please correct it

# Set up development environment
git clone https://github.com/CronusL-1141/AI-company.git
cd AI-company/ai-team-os
pip install -e ".[dev]"
pytest tests/

Before submitting a PR, please ensure:

ruff check src/ passes
mypy src/ has no new errors
Relevant tests pass

License

MIT License — see LICENSE

AI Team OS — The AI company that runs while you sleep.

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