76fbd48849
* fix(skills): measure draft dirtiness against a seeded baseline (MUL-5645) The detail page inferred "the user edited something" from "the draft differs from the latest server skill". That difference has two independent causes — the user typed, or the server moved — and the page could not tell them apart, so it read both as a local edit. Two user-visible failures came out of it: - A description ending in whitespace (what `description: |` frontmatter yields, so every imported skill) compared unequal to itself, because the dirty check trimmed the draft side and not the server side. The page opened permanently dirty and Discard reseeded the same value, so the save bar could not be dismissed at all — only Save cleared it, by rewriting the stored description. - Any remote update to an open skill was taken for a local edit, so the page raised the conflict banner and refused to reseed. The editor stayed frozen on pre-update text with no way to see what had changed, and saving from there pushed the stale draft back over the newer version. Record the seeded snapshot in `baselineRef` and compare against that instead. With a baseline the two causes separate: `draft !== baseline` is a local edit, and a new `updated_at` with no local edits is just a remote update, which now reseeds silently. The conflict banner is left for the case it was written for — a remote update landing on real unsaved work. `toDraft` also trims name and description at the single seam where server data becomes a draft, matching what Save persists, so later comparisons are plain equality rather than a trim both sides have to remember. Content and file bodies are not normalized: whitespace in a SKILL.md body is content. File sets are compared through a path-sorted signature, since GET sorts files by path while PUT echoes request order and that difference is not a content change. Four of the five regression tests fail against the previous implementation; the fifth covers the true-conflict path, which was already correct and must stay that way. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Co-authored-by: multica-agent <github@multica.ai> * fix(skills): trim frontmatter name and description at the parse seam (MUL-5645) Both fields are single-line labels everywhere they are consumed, but YAML clip chomping gives `description: |` and `description: >` a trailing newline, so imports stored a description that differed from its own trimmed form. The detail page no longer depends on this — it normalizes when it seeds a draft — but leaving it means every new import keeps writing the padded value, and any future consumer that compares a stored description to a trimmed one inherits the same trap. Trimming here covers all four import paths (GitHub, skills.sh, archive, runtime-local) in one place rather than asking each to remember. Callers that need the raw SKILL.md still have it: `content` is stored untouched. Defensive only. Reverting this commit alone does not reintroduce the bug. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Co-authored-by: multica-agent <github@multica.ai> * fix(skills): release the conflict when the user reverts their own edits (MUL-5645) Review catch on the previous commit. Once a conflict was raised, the seed effect only reconsidered when a new server version arrived, so a user who resolved the conflict by hand — retyping the field back to what it was — got stuck: the draft was clean again, and because the save bar renders only while dirty, its Discard button unmounted. That left the banner sitting above stale text with no control left to dismiss it, and no way forward short of a reload. This state is a regression from measuring dirtiness locally. Previously the draft was compared against the moved server value, so reverting still counted as dirty and Discard stayed on screen. Re-run the decision on draft changes too. When the local edits go away there is nothing left to protect, so the page adopts the server version and clears the banner — the same outcome as the never-edited case, reached a moment later. The true-conflict path is unchanged, and its regression test still passes, which is what keeps this from over-correcting into "always release". Reseeding also grew a third caller, so the four pieces that have to move together — draft, baseline, seeded key, conflict flag — are now assigned in exactly one place, `adoptServerVersion`, used by first load, silent refresh, Save and Discard alike. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Co-authored-by: multica-agent <github@multica.ai> --------- Co-authored-by: Claude Opus 5 <noreply@anthropic.com> Co-authored-by: multica-agent <github@multica.ai>
Multica
Your next 10 hires won't be human.
The open-source managed agents platform.
Turn coding agents into real teammates — assign tasks, track progress, compound skills.
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What is Multica?
Multica turns coding agents into real teammates. Assign issues to an agent like you'd assign to a colleague — they'll pick up the work, write code, report blockers, and update statuses autonomously.
No more copy-pasting prompts. No more babysitting runs. Your agents show up on the board, participate in conversations, and compound reusable skills over time. Think of it as open-source infrastructure for managed agents — vendor-neutral, self-hosted, and designed for human + AI teams. Works with Claude Code, Codex, CodeBuddy, GitHub Copilot CLI, OpenCode, OpenClaw, Hermes, Pi, Cursor Agent, Kimi, Kiro CLI, Antigravity, Qoder CLI, and Trae CLI.
For larger teams, Squads add a stable routing layer: assign work to a group led by an agent, and the leader delegates to the right member.
Why "Multica"?
Multica — Multiplexed Information and Computing Agent.
The name is a nod to Multics, the pioneering operating system of the 1960s that introduced time-sharing — letting multiple users share a single machine as if each had it to themselves. Unix was born as a deliberate simplification of Multics: one user, one task, one elegant philosophy.
We think the same inflection is happening again. For decades, software teams have been single-threaded — one engineer, one task, one context switch at a time. AI agents change that equation. Multica brings time-sharing back, but for an era where the "users" multiplexing the system are both humans and autonomous agents.
In Multica, agents are first-class teammates. They get assigned issues, report progress, raise blockers, and ship code — just like their human colleagues. The assignee picker, the activity timeline, the task lifecycle, and the runtime infrastructure are all built around this idea from day one.
Like Multics before it, the bet is on multiplexing: a small team shouldn't feel small. With the right system, two engineers and a fleet of agents can move like twenty.
Features
Multica manages the full agent lifecycle: from task assignment to execution monitoring to skill reuse.
- Agents as Teammates — assign to an agent like you'd assign to a colleague. They have profiles, show up on the board, post comments, create issues, and report blockers proactively.
- Squads — group agents (and humans) under a leader agent and assign work to the squad. The leader decides who should pick it up, so routing stays stable as the team grows.
@FrontendTeaminstead of@alice-or-bob-or-carol. - Autonomous Execution — set it and forget it. Full task lifecycle management (enqueue, claim, start, complete/fail) with real-time progress streaming via WebSocket.
- Autopilots — schedule recurring work for agents. Cron triggers, webhooks, or manual runs — each autopilot creates the issue and routes it to an agent automatically, so daily standups, weekly reports, and periodic audits run themselves.
- Reusable Skills — every solution becomes a reusable skill for the whole team. Deployments, migrations, code reviews — skills compound your team's capabilities over time.
- Unified Runtimes — one dashboard for all your compute. Local daemons and cloud runtimes, auto-detection of available CLIs, real-time monitoring.
- Multi-Workspace — organize work across teams with workspace-level isolation. Each workspace has its own agents, issues, and settings.
Quick Install
macOS / Linux
Homebrew (recommended)
brew install multica-ai/tap/multica
Use brew upgrade multica-ai/tap/multica to keep the CLI current.
Install script
curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash
Use this if Homebrew is not available. The script installs the Multica CLI on macOS and Linux by using Homebrew when it is on PATH, otherwise it downloads the binary directly.
Then configure, authenticate, and start the daemon in one command:
multica setup # Connect to Multica Cloud, log in, start daemon
Self-hosting? Add
--with-serverto deploy a full Multica server on your machine:curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash -s -- --with-server multica setup self-hostThis pulls the official Multica images from GHCR (latest stable by default). Requires Docker. See the Self-Hosting Guide for details. If the selected GHCR tag has not been published yet, fall back to
make selfhost-buildfrom a checkout.
Windows (PowerShell)
PowerShell
irm https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.ps1 | iex
Then configure, authenticate, and start the daemon in one command:
multica setup # Connect to Multica Cloud, log in, start daemon
Self-hosting? Set the
MULTICA_MODEenvironment variable towith-serverbefore running the installer to deploy a full Multica server on your machine:$env:MULTICA_MODE="with-server"; irm https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.ps1 | iex multica setup self-hostThis pulls the official Multica images from GHCR (latest stable by default). Requires Docker. See the Self-Hosting Guide for details.
Getting Started
1. Set up and start the daemon
multica setup # Configure, authenticate, and start the daemon
The daemon runs in the background and auto-detects agent CLIs (claude, codex, codebuddy, copilot, opencode, openclaw, hermes, pi, cursor-agent, kimi, kiro-cli, agy, qodercli, qoderclicn, traecli) on your PATH.
2. Verify your runtime
Open your workspace in the Multica web app. Navigate to Settings → Runtimes — you should see your machine listed as an active Runtime.
What is a Runtime? A Runtime is a compute environment that can execute agent tasks. It can be your local machine (via the daemon) or a cloud instance. Each runtime reports which agent CLIs are available, so Multica knows where to route work.
3. Create an agent
Go to Settings → Agents and click New Agent. Pick the runtime you just connected and choose a provider (Claude Code, Codex, CodeBuddy, GitHub Copilot CLI, OpenCode, OpenClaw, Hermes, Pi, Cursor Agent, Kimi, Kiro CLI, Antigravity, Qoder CLI, or Trae CLI). Give your agent a name — this is how it will appear on the board, in comments, and in assignments.
4. Assign your first task
Create an issue from the board (or via multica issue create), then assign it to your new agent. The agent will automatically pick up the task, execute it on your runtime, and report progress — just like a human teammate.
CLI
The multica CLI connects your local machine to Multica — authenticate, manage workspaces, and run the agent daemon.
| Command | Description |
|---|---|
multica login |
Authenticate (opens browser) |
multica daemon start |
Start the local agent runtime |
multica daemon status |
Check daemon status |
multica setup |
One-command setup for Multica Cloud (configure + login + start daemon) |
multica setup self-host |
Same, but for self-hosted deployments |
multica workspace list |
List your workspaces (current is marked with *) |
multica workspace switch <id|slug> |
Switch the default workspace for this profile |
multica issue list |
List issues in your workspace |
multica issue create |
Create a new issue |
multica update |
Update to the latest version |
See the CLI and Daemon Guide for the full command reference.
Architecture
┌──────────────┐ ┌──────────────┐ ┌──────────────────┐
│ Next.js │────>│ Go Backend │────>│ PostgreSQL │
│ Frontend │<────│ (Chi + WS) │<────│ (pgvector) │
└──────────────┘ └──────┬───────┘ └──────────────────┘
│
┌──────┴───────┐
│ Agent Daemon │ runs on your machine
└──────────────┘ (Claude Code, Codex, CodeBuddy, GitHub Copilot CLI,
OpenCode, OpenClaw, Hermes, Pi, Cursor Agent,
Kimi, Kiro CLI, Antigravity, Qoder CLI, Trae CLI)
| Layer | Stack |
|---|---|
| Frontend | Next.js 16 (App Router) |
| Backend | Go (Chi router, sqlc, gorilla/websocket) |
| Database | PostgreSQL 17 with pgvector |
| Agent Runtime | Local daemon executing Claude Code, Codex, CodeBuddy, GitHub Copilot CLI, OpenCode, OpenClaw, Hermes, Pi, Cursor Agent, Kimi, Kiro CLI, Antigravity, Qoder CLI, or Trae CLI |
Development
For contributors working on the Multica codebase, see the Contributing Guide.
Prerequisites: Node.js v20+, pnpm v10.28+, Go v1.26+, Docker
make dev
make dev auto-detects your environment (main checkout or worktree), creates the env file, installs dependencies, sets up the database, runs migrations, and starts all services.
See CONTRIBUTING.md for the full development workflow, worktree support, testing, and troubleshooting.
An iOS mobile client lives in apps/mobile/ — see its README for how to build it onto your own iPhone.
License
Multica License — the complete Apache License 2.0 text incorporated together with additional conditions — see NOTICE for attribution notices.
- Providing Multica as a hosted service to third parties, or embedding it in a commercially distributed product, requires a commercial license obtained from the producer (condition 1a).
- Unless the producer has granted a written branding waiver, the Multica LOGO, product name, and copyright information may not be removed or modified in a Multica user interface. The user interface is defined by derivation — including
apps/web/,apps/desktop/,apps/mobile/,packages/views/, andpackages/ui/— and covers raw source, the frontend container image, and compiled desktop and mobile binaries (condition 1b). - Non-interface use (running only the
server/backend, the daemon, or the CLI) is exempt from the branding condition, but must retain the source and NOTICE attribution and state that the product is built on Multica, with a link back to this repository (condition 1c). - A branding waiver and a commercial license are separate grants; neither implies the other (condition 1d).