Jiayuan Zhang ad09baa045 feat(agents): add runtime machine filter to Agents tab (MUL-2846) (#3580)
* feat(agents): add runtime machine filter to Agents tab (MUL-2846)

Add a dropdown filter to the Agents tab toolbar that lets the user
narrow the list to agents bound to a specific runtime machine. The
filter reuses `buildRuntimeMachines` from the runtimes package so the
machine grouping (Local / Remote / Cloud) matches the Runtimes page
sidebar, and the per-machine agent counts respect the current scope
(Mine/All) so the numbers reflect what the user would see if they
clicked the row.

Only rendered in the Active view; the Archived view's toolbar is
unchanged. If the selected machine is GC'd while the user is on the
page (daemon stopped, runtime deleted), the filter auto-resets to
'All runtimes' instead of leaving the list empty. The no-matches state
now surfaces 'No agents on <machine>' when the machine filter is the
reason for zero results.

Adds new `runtime_filter` and `no_matches.runtime_filtered` /
`no_matches.search_runtime_filtered` i18n keys in en, zh-Hans, and
ko. 7 new unit tests in
`runtime-machine-filter-dropdown.test.tsx`.

Co-authored-by: multica-agent <github@multica.ai>

* fix(agents): address code review on runtime machine filter

- Plumb localDaemonId / localMachineName / hasLocalMachine / currentUserId
  through AgentsPage → buildRuntimeMachines so the Local section and
  device-name consolidation match the Runtimes page on both web and
  Desktop. Adds a DesktopAgentsPage wrapper that bridges daemonAPI the
  same way DesktopRuntimesPage does.
- Make the 'All runtimes' badge use the in-scope total instead of
  summing per-machine counts, so an agent bound to a GC'd runtime
  doesn't silently vanish from the count.
- Move Date.now() out of the machines useMemo into a useState lazy
  init so the snapshot stays stable per mount.
- Drop unused i18n keys (all_description / this_machine / reset) from
  runtime_filter in en / zh-Hans / ko.
- Add a regression test for the All-runtimes badge divergence.

Co-authored-by: multica-agent <github@multica.ai>

* fix(agents): machine-scoped availability counts + Base UI menu items

Follow-up to the previous code-review round (Emacs review at 1144b6023).

#1 (medium) — Availability counts now respect the selected machine.
Introduce an inScopeOnMachine memo (inScope narrowed by the selected
runtime machine, but NOT by availability chip or search) and use it as
the base for both availabilityCounts and the AvailabilityFilterRow's
totalCount, so the chips reflect 'agents on this machine' once a
machine is selected. filteredAgents is now derived from inScopeOnMachine
so the availability chip and search further refine within the machine
scope. The dropdown's 'All runtimes' badge still uses inScope.length —
it's the count the user would see if they cleared the filter, so it
should stay unfiltered.

#2 (low) — Dropdown rows now use DropdownMenuItem instead of raw <button>.
Replaces the bare <button> in RuntimeMachineFilterItem with the
shared DropdownMenuItem wrapper (Base UI Menu.Item). The rows are now
registered as proper menu items: keyboard navigation (arrow keys, Enter,
Space), typeahead, ARIA role='menuitem' semantics, and auto-close on
selection (closeOnClick: true) all work. Active styling is preserved
via data-active, and a data-highlighted variant on the inactive style
matches Base UI's keyboard-focus appearance.

Tests updated to use role-based queries (getByRole('menuitem')) and
add a regression that verifies the menu is properly registered with
Base UI.

Co-authored-by: multica-agent <github@multica.ai>

---------

Co-authored-by: Lambda <lambda@multica.ai>
Co-authored-by: multica-agent <github@multica.ai>
Co-authored-by: MiniMax M3 <M3@multica.local>
2026-06-01 10:17:56 +08:00

Multica — humans and agents, side by side

Multica

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.

CI GitHub stars

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, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, and Kiro 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.

Multica board view

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. @FrontendTeam instead 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

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-server to 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-host

This 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-build from a checkout.


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, copilot, openclaw, opencode, hermes, gemini, pi, cursor-agent, kimi, kiro-cli, agy) 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, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, Kiro CLI, or Antigravity). 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, GitHub Copilot CLI,
                                        OpenCode, OpenClaw, Hermes, Gemini,
                                        Pi, Cursor Agent, Kimi, Kiro 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, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, or Kiro 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.

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