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개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
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1분 만에 확인하기Free app made for creating and managing your AI agents locally on your machine. Built-in memory and skills keep context small and usage low.
저장소 README에서 가져옴
README 전체를 불러오는 중입니다.
README 전문 보기 ↗AI teammates for work and imagination.
Automate the routine. Make room for the creative. Mawl is an open-source, self-hosted home for a small team of AI agents, with your models, your keys, and your work on your machine.
Get started · What's working · Development · Documentation
In Mawl, an agent is a teammate: a role you shape, with its own persona and choice of model. The desktop app hosts the server and database locally; a headless Docker setup is available too.
The wider vision is a team that can carry work forward together. A researcher gathers the useful details. A writer turns them into a brief. A designer brings the direction to a canvas. You steer the work, review the result, and decide what happens next.
| Direction | What it makes room for |
|---|---|
| Workflows that keep moving | Repeatable routines, scheduled work, and focused handoffs between teammates. |
| A creative process you can see | Canvases for mockups, sites, and graphics, with dedicated animation and video workflows planned later. |
| Memory with a purpose | Decisions, preferences, useful history, and reusable skills you can inspect and edit. |
| Context that earns its place | Cache-aware prompt assembly, selective recall, compact handoff notes, and context budgets designed to avoid unnecessary token use. |
| A computer when the work needs one | Optional sandboxed terminal or desktop computers, with visible activity and takeover on the roadmap. |
| You stay in the loop | Planned policy gates, approvals, and an audit trail keep sensitive actions reviewable. |
| A space that's yours | Your model providers, local conversation storage, and optional sandboxed teammate computers. |
These are product directions, not a list of shipped features. Actual token usage depends on your model and workload. The current implementation and next steps are below.
Mawl is in active development. The foundations include:
The full agent workflow, teammate-to-teammate communication, optional computers, long-term memory, schedules, and canvases are being built toward. Telegram, Discord, and mobile access are later work. See the implementation plan for the precise status; the desktop-first decision record explains the architecture's direction.
Provider foundations cover Anthropic, OpenAI, OpenRouter, Ollama, and compatible APIs. ChatGPT and Claude Code account-based paths and their limitations are documented in Running Mawl. Online models receive the context needed to answer; choosing a local model is a separate decision from storing conversations locally.
The documented headless setup needs Docker with Compose v2. Run these commands from the repository root.
For a fresh setup, copy infra/compose/.env.example to infra/compose/.env and set a random MAWL_DB_PASSWORD. If you already have a database and an .env, keep its existing password. The running guide includes password-generation commands for Bash and PowerShell.
docker compose -f infra/compose/docker-compose.yml up -d --build
Open localhost:7420. The first start builds the app, waits for Postgres, and applies migrations. The browser asks for the owner token generated by the server; follow the owner-token instructions to retrieve it and sign in.
Check the services and follow the logs:
docker compose -f infra/compose/docker-compose.yml ps
docker compose -f infra/compose/docker-compose.yml logs -f server
Running Mawl covers provider sign-in, ports, configuration, persistent data, troubleshooting, and reset. The Windows desktop host is the main product direction; this Compose guide remains the documented way to explore the headless app from source.
apps/
server/ HTTP + WebSocket server, run engine, providers
web/ React interface
desktop/ Tauri desktop host
mobile/ Expo app foundations; mobile delivery is planned
packages/
contracts/ zod schemas, events, and the oRPC contract
core/ providers, prompt assembly, and shared agent logic
db/ Drizzle schema and migrations
memory/ memory-system package
sandbox/ teammate-computer package
ui/ design tokens and accent engine
... client, mascot, channels, native UI, and test utilities
infra/ Docker Compose, desktop packaging, and computer infrastructure
design/ brand assets and visual references
site/ landing page (static, deployed to Cloudflare Pages) and local preview
docs/ product, architecture, design, and implementation guides
Use Node 24 and pnpm 10 through Corepack. Install dependencies from the root:
corepack pnpm i
Prefer checks scoped to the package or files you changed. For example:
corepack pnpm --filter @mawl/web typecheck
corepack pnpm exec biome check site
The workspace commands remain available when you need a broader check:
corepack pnpm lint
corepack pnpm typecheck
corepack pnpm test
For the current landing-page design, run node site/preview.mjs and open localhost:4173. It uses local fonts and assets and needs no build step.
CLAUDE.md covers repository conventions, scoped testing, and the development workflow. The plan is the source of truth for implementation status.
| Guide | Start here when you want to… |
|---|---|
| Product specification | Understand who Mawl is for and what it aims to do. |
| Running Mawl | Start the app, connect a provider, inspect logs, or manage data. |
| Architecture | Follow the server, clients, event flow, and runtime boundaries. |
| Desktop-first decisions | Understand the desktop host and current technical direction. |
| Memory and context | Explore recall, compaction, prompt caching, and context budgets. |
| Canvases | Read the proposed design, graphics, site, and motion workspace. |
| Design system | Work with the interface's tokens, character, and interaction principles. |
| Implementation plan | See what is built, in progress, and still ahead. |
Mawl is licensed under Apache 2.0. Third-party notices are in NOTICE.
Good work, made together.