75c11db048
* feat(agent): discover codebuddy models over ACP instead of scraping --help (MUL-5549) CodeBuddy speaks ACP, and `session/new` answers with a structured catalog under models.availableModels plus a currentModelId — exactly the shape the shared parseACPSessionNewModels already reads for Copilot / Kimi / Kiro / Qoder / Grok / TRAE. Scraping the `--model` line out of `codebuddy --help` was never necessary. The help text carried IDs and nothing else, which cost us three things: - Labels were guessed from the ID and were simply wrong. `kimi-k3-1` rendered as "Kimi K3 1" where the CLI says Kimi-K3; `deepseek-v3-2-volc` as "Deepseek V3 2 Volc" where the CLI says DeepSeek-V3.2. - The default model was a "first entry wins" guess rather than the advertised currentModelId. - The effort catalog needed a second regex over the same output. All three come from the handshake now. The effort catalog rides along in the same session/new response as the `thought_level` config option, so it costs no extra process — which also retires the "at most one --help per request" constraint added in #6196, because --help is no longer run at all. One trap worth naming: thought_level advertises `enabled` ("On (default)") alongside the six real levels, but `--effort enabled` is not a valid command line — the daemon passes the selected level straight to the flag. Advertised levels are filtered against the flag's accepted set, and a currentValue outside that set (the default `enabled`) becomes an empty DefaultLevel, which the UI renders as a generic "Default" instead of a value we cannot pass through. Two adjacent inaccuracies surfaced while confirming the real level set against CodeBuddy 2.130.0, both fixed here: the static effort fallback omitted `minimal` and `max`, and so did the server-side IsKnownThinkingValue gate — so the server rejected two levels the CLI genuinely accepts. Discovery keeps its fallback, still marked Fallback so it can never be cached as authoritative (#6196). That covers the not-logged-in case, which is deliberately NOT special-cased with an auth step: the catalog came back without calling authenticate on a logged-in CLI, and inventing an auth branch we cannot exercise would be speculation. Removes codebuddyModelRe, parseCodebuddyModels, codebuddyModelLabel, codebuddyModelProvider, codebuddyEffortRe, parseCodebuddyEffortHelp, codebuddyEffortSuperset, codebuddyHelpOutput and its 60s help cache. Co-authored-by: multica-agent <github@multica.ai> * fix(agent): keep codebuddy's vendor grouping after the ACP migration (MUL-5549) Review nit, and a real regression in the previous commit. Dropping codebuddyModelProvider looked like removing dead code, but it was the only thing populating Model.Provider for CodeBuddy — and the picker groups on that field. acpModelEntry can only recover a vendor from a `vendor:model` id. CodeBuddy's are bare (`glm-5.2`, `kimi-k3-1`), so every model came back with an empty Provider, and model-dropdown renders the empty group with no header at all: all 16 models would have collapsed into one unlabelled list where main shows Zhipu / Kimi / MiniMax / DeepSeek / Hunyuan sections. Restores the prefix inference as a post-pass over the ACP catalog, exactly the shape discoverCopilotModels already uses for the same reason. Verified against the real CLI: all 16 models land in five vendor groups with none ungrouped. Tests assert the vendor for every id CodeBuddy 2.130.0 advertises plus the static fallback ids, and that the fallback entries' hardcoded providers agree with the inference. Removing the post-pass fails them. Co-authored-by: multica-agent <github@multica.ai> --------- Co-authored-by: Bohan-J <bohan@devv.ai> 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, 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
Modified Apache 2.0 (with commercial restrictions) — 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).