AIPass

Your AI agents remember yesterday.

A local multi-agent framework where your AI assistants keep their memory between sessions, work together on the same codebase, and never ask you to re-explain context.

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Contents

• The Problem
• What AIPass Does
• Quick Start
• What You Can Do
• How It Works
• The 15 Branches
• CLI Support
• Platform Support
• Project Status
• Requirements
• Subscriptions & Compliance

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The Problem

Your AI has memory now. It remembers your name, your preferences, your last conversation. That used to be the hard part. It isn't anymore.

The hard part is everything that comes after. You're still one person talking to one agent in one conversation doing one thing at a time. When the task gets complex, you become the coordinator — copying context between tools, dispatching work manually, keeping track of who's doing what. You are the glue holding your AI workflow together, and you shouldn't have to be.

Multi-agent frameworks tried to solve this. They run agents in parallel, spin up specialists, orchestrate pipelines. But they isolate every agent in its own sandbox. Separate filesystems. Separate worktrees. Separate context. One agent can't see what another just built. Nobody picks up where a teammate left off. Nobody works on the same project at the same time. The agents don't know each other exist.

That's not a team. That's a room full of people wearing headphones.

What's missing isn't more agents — it's presence. Agents that have identity, memory, and expertise. Agents that share a workspace, communicate through their own channels, and collaborate on the same files without stepping on each other. Not isolated workers running in parallel. A persistent society with operational rules — where the system gets smarter over time because every agent remembers, every interaction builds on the last, and nobody starts from zero.

What AIPass Does

AIPass gives your AI agents persistent identity and memory. Each agent lives in your filesystem, remembers its history, and communicates with other agents through a shared mailbox system. You talk to one orchestrator. It dispatches specialists. Results come back. Context survives.

You <-> devpulse (orchestrator) <-> 14 specialist agents

Say "hi" tomorrow and pick up exactly where you left off.

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Quick Start

git clone https://github.com/AIOSAI/AIPass.git
cd AIPass
./setup.sh        # Creates venv, installs, bootstraps 15 agents
drone systems     # See all agents

Then start working:

cd src/aipass/devpulse
claude

Talk to devpulse. Ask what's happening. Dispatch work. Come back later.

Linux (fully tested)

Works out of the box. This is the primary development platform.

./setup.sh

macOS (untested, should work)

setup.sh should work on macOS. Known issue: Apple Silicon Macs may need Homebrew path adjustment for symlinks.

brew install python@3.10
./setup.sh

Windows

WSL2 (recommended): setup.sh runs with zero changes inside WSL2.

Native Windows: Has been tested on Windows 10 with most functionality working. No setup.ps1 yet — manual setup required.

Docker

docker build -t aipass .
docker run -d -p 8080:8080 aipass

Opens a code-server IDE with Python, Node.js, and Claude Code pre-installed.

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What You Can Do

• Never re-explain context. Your agents remember across sessions, days, weeks. Memory persists in .trinity/ files and rolls over to vector search when full.
• Dispatch work to specialists. Send a task to the right agent. It investigates, builds, tests, and reports back. You don't wait — start something else.
• Work in teams on the same files. 15 agents share one filesystem. No git worktrees isolating them. A planning system prevents conflicts.
• Enforce quality automatically. 33 automated standards checks run across every agent. Code stays consistent at scale.
• Use any AI CLI. Claude Code, Codex, or Gemini CLI. Same hooks, same identity, same commands.
• Switch context freely. Building something complex? Pause it. "Hey, investigate this other thing." Come back when ready.
• Scale it your way. Add agents. Add capabilities. The framework grows with you.

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How It Works

Every agent has three things: an identity (who it is), memory (what it knows), and a mailbox (how it communicates).

src/aipass/<agent>/
├── .trinity/           # Identity + memory (persists across sessions)
├── .ai_mail.local/     # Mailbox (receives tasks, sends results)
├── apps/               # What this agent can do
└── README.md

You talk to devpulse (the orchestrator). It knows every agent's specialty and dispatches work:

drone @ai_mail dispatch @memory "Archive old sessions" "Find sessions older than 30 days and archive them"
drone @seedgo audit aipass                    # Run quality checks on everything
drone @flow create . "Refactor auth module"   # Create a work plan

Pattern: drone @branch command [args] — one line, non-interactive.

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The 15 Agents

Branch	What It Does
devpulse	Orchestrator — you talk to this one. It coordinates everyone else.
drone	Routes commands to the right branch. The postal service.
memory	Long-term storage. Vector search over everything branches have learned.
ai_mail	Messaging between branches. Dispatch tasks, get replies.
flow	Work plans — tracks what's being built and what's being designed.
seedgo	Quality enforcement — 33 automated checks across all branches.
prax	Monitoring — logs, dashboards, real-time session tracking.
trigger	Event system — things that happen automatically when conditions are met.
spawn	Creates new branches from templates.
cli	Terminal formatting and rich output.
daemon	Background scheduler with cron jobs.
backup	Snapshots, versioned backups, Google Drive sync.
api	LLM access via OpenRouter (optional).
commons	Community space where branches share updates and discuss.
skills	Reusable capabilities that branches can invoke.

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CLI Support

AIPass works with three AI coding CLIs. Claude Code is the most tested.

CLI	Autonomous Mode	Status
Claude Code	claude -p "prompt" --permission-mode bypassPermissions	Fully tested
Codex	codex exec "prompt" --approval-mode never	Integrated, less tested
Gemini CLI	gemini -p "prompt" --approval-mode=yolo	Integrated, less tested

setup.sh auto-detects which CLIs are installed and configures hooks for each.

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Platform Support

Platform	Status
Linux	Fully tested
Windows (WSL2)	Expected to work, zero changes needed
Windows (native)	Partial testing on Windows 10
macOS	Untested, should work

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Project Status

Beta. Actively developed by a solo developer + AI team.

Metric	Value
Agents	15
Quality standards	33
Tests	4,900+
PRs merged	192+
Development sessions	76

For detailed session history, see HERALD.md.

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Requirements

• Python 3.10+
• Linux recommended (macOS should work; Windows via WSL2)
• At least one AI CLI: Claude Code (recommended), Codex, or Gemini CLI
• sudo access (for global CLI symlinks)
• API keys optional (only for the api branch — OpenRouter/OpenAI)

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Subscriptions & Compliance

Use your existing subscription

AIPass runs on your existing CLI subscription — Claude Pro/Max, Codex, or Gemini. No API keys required for core functionality. No extra costs. Your subscription covers everything.

This works because AIPass runs each CLI as an official subprocess — the same binary you'd run yourself in a terminal. It doesn't extract credentials, proxy API calls, or intercept tokens. Your subscription stays within the provider's infrastructure at all times.

This is different from tools like OpenClaw that were restricted by Anthropic for extracting subscription OAuth tokens and routing workloads outside the official CLI. AIPass doesn't do that — it enhances the CLI through officially supported extension points (hooks, CLAUDE.md, AGENTS.md, GEMINI.md).

What AIPass does NOT do

• Extract or redirect subscription OAuth tokens
• Intercept CLI-to-provider communication
• Bypass rate limits or prompt caching
• Impersonate official CLI clients

Claude Code is proprietary but officially supports hooks and subprocess usage. Codex and Gemini CLI are open source (Apache 2.0). No provider forbids this usage pattern.

API keys are only needed for the optional api agent (OpenRouter/OpenAI). For server/automated deployments, API key authentication is recommended per Anthropic's guidance.

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