a67e533742
Adds a first-class `model` field to agents so users can pick the LLM model
from the create / settings UI instead of editing custom_env / custom_args.
The previous "set MULTICA_<PROVIDER>_MODEL env var on the daemon" approach
forced one model per provider per machine and was easy to misconfigure
(e.g. -m as a custom_arg breaks codex app-server initialization).
Backend (server/pkg/agent):
- New `agent.ListModels(provider, path)` returns the models supported by a
provider. Static catalogs for claude, codex, gemini, cursor, copilot;
dynamic discovery for opencode (`opencode models`), pi (`pi --list-models`),
openclaw (`openclaw agents list`); 60s TTL cache + empty-list fallback on
failure. Hermes returns an empty list and `ModelSelectionSupported=false`
because its model is configured out-of-band.
- `agent.DefaultModel(provider)` returns the recommended default per
provider (Sonnet 4.6 for claude, GPT-5.4 for codex, Gemini 2.5 Pro for
gemini, composer-1.5 for cursor); copilot/openclaw/hermes deliberately
have no default. The static catalog tags one entry per provider with
`Default: true` so the UI can render a badge.
- For openclaw, opts.Model is mapped to `--agent <name>` since the CLI
rejects `--model` outright; custom_args `--agent` still wins for
back-compat.
Daemon protocol (server/internal/daemon):
- Heartbeat response carries an optional `pending_model_list` request
(same pattern as PingStore / UpdateStore). The daemon resolves models
via `agent.ListModels`, including the `supported` flag, and reports
back via /api/daemon/runtimes/{id}/models/{requestId}/result.
- Task dispatch uses a three-tier fallback for the runtime model:
agent.model → MULTICA_<PROVIDER>_MODEL env → agent.DefaultModel(provider).
Server API (server/internal/handler):
- `agent.model` is a new column (migration 050) and surfaces in
Agent / CreateAgent / UpdateAgent payloads.
- New endpoints under /api/runtimes/{id}/models: POST to initiate
discovery, GET to poll the request, plus the daemon-side report
endpoint above.
CLI (server/cmd/multica):
- `multica agent create / update --model <id>`. Help copy steers users
away from passing --model via --custom-args, which fails on codex
(app-server mode) and openclaw.
Frontend (packages/core, packages/views):
- `Agent.model`, `RuntimeModel`, `RuntimeModelListRequest`,
`RuntimeModelsResult` types.
- `runtimes/models.ts` exports `runtimeModelsOptions(runtimeId)` which
initiates discovery and polls the request to completion (500ms
cadence, 30s ceiling).
- New `ModelDropdown` (packages/views/agents) — searchable popover,
provider grouping, creatable manual entry, "default" badge on the
shipped recommendation, disabled state when the provider reports
`supported=false` (Hermes), and clears any stale model value in that
case to avoid persisting a ghost configuration.
- Wired into create-agent-dialog and the agent settings tab.
Verification:
- gofmt clean on touched files
- `go build ./... && go test ./...` (server) green; new openclaw and
models_test cases included
- `pnpm typecheck` green across all 6 packages
Closes the immediate UX gap behind MUL-1151. DeepSeek V4 (or any new
model) becomes a zero-code addition: add it to the relevant static
catalog, or rely on the creatable input for one-off use.
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.
Website · Cloud · X · Self-Hosting · Contributing
English | 简体中文
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, OpenClaw, OpenCode, Hermes, Gemini, Pi, and Cursor Agent.
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.
- Autonomous Execution — set it and forget it. Full task lifecycle management (enqueue, claim, start, complete/fail) with real-time progress streaming via WebSocket.
- 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.
macOS / Linux (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.
Windows (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? 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-hostRequires 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, openclaw, opencode, hermes, gemini, pi, cursor-agent) 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, OpenClaw, OpenCode, Hermes, Gemini, Pi, or Cursor Agent). 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.
Multica vs Paperclip
| Multica | Paperclip | |
|---|---|---|
| Focus | Team AI agent collaboration platform | Solo AI agent company simulator |
| User model | Multi-user teams with roles & permissions | Single board operator |
| Agent interaction | Issues + Chat conversations | Issues + Heartbeat |
| Deployment | Cloud-first | Local-first |
| Management depth | Lightweight (Issues / Projects / Labels) | Heavy governance (Org chart / Approvals / Budgets) |
| Extensibility | Skills system | Skills + Plugin system |
TL;DR — Multica is built for teams that want to collaborate with AI agents on real projects together.
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 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, OpenCode,
OpenClaw, Hermes, Gemini,
Pi, Cursor Agent)
| 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, OpenClaw, OpenCode, Hermes, Gemini, Pi, or Cursor Agent |
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.