* fix(daemon): scope claim-time comment fetches to the task's workspace (MUL-4252) The daemon claim path embeds the triggering comment and every coalesced comment's full text into the agent prompt, but fetched them with an unscoped `GetComment(id)` — a task row carrying a foreign comment UUID would pull another workspace's comment text into the prompt. On a shared SaaS backend (tens of thousands of workspaces in one DB) that is a tenant boundary hole, latent today only because task rows are server-written. Switch all three claim/reconcile GetComment calls to GetCommentInWorkspace, scoped by the runtime's workspace (claim path) or the issue's workspace (completion reconcile). The task's issue workspace is already asserted equal to the runtime workspace, so same-workspace delivery is unchanged; a foreign UUID now resolves to "missing" and is skipped — matching buildCoalescedCommentData's documented behavior. Adds DB-backed claim tests: same-workspace trigger comment is still delivered; a foreign-workspace comment's content never surfaces. Co-authored-by: multica-agent <github@multica.ai> * fix(cli): extend the workdir guardrail to --attachment paths (MUL-4252) #5167 fenced --description-file/--content-file to the working directory but left --attachment uncovered — the same /tmp stale-file leak in image form: an agent that writes chart.png to a machine-shared path and attaches it could upload another run's (possibly another workspace's) stale file. Apply ensureAttachmentWithinWorkdir to each local --attachment path in `issue create` and `comment add` (URL values are still skipped upstream), reusing #5167's symlink-resolving fileWithinWorkingDir and the existing --allow-external-file escape hatch. Rejection happens before the issue is created, so a bad path never yields a half-created issue. Co-authored-by: multica-agent <github@multica.ai> * fix(service): scope trigger-summary + originator resolution to the task's workspace (MUL-4252) PR review P1: the claim-time full-comment fetch was already scoped, but the trigger_summary snapshot (first ~200 chars) still leaked. On the real enqueue/merge paths a foreign comment UUID flowed through buildCommentTriggerSummary / resolveOriginatorFromTriggerComment, which used an unscoped GetComment; the truncated text was stored on the task row and later returned in the claim / task-history response (handler/agent.go trigger_summary). Thread the issue's workspace through both helpers (and their exported merge-path wrappers) and switch to GetCommentInWorkspace, so a cross-workspace comment resolves to "missing": trigger_summary stays NULL and no foreign originator is inherited. Every caller already has the issue's WorkspaceID in scope (enqueue, mention/leader, deferred fallback, merge, completion reconcile). Rework the claim test to drive the REAL TaskService.EnqueueTaskForIssue path (which snapshots the summary) and assert the stored row's trigger_summary + originator_user_id stay NULL and the claim response carries neither the foreign body nor the foreign summary. Verified the test fails when the summary fetch is left unscoped. Co-authored-by: multica-agent <github@multica.ai> * fix(cli): validate all --attachment paths before uploading any in comment add (MUL-4252) PR review P2: `issue comment add` checked-read-uploaded each attachment in one loop, so a valid workdir attachment followed by an invalid (external / symlink-escaping) one uploaded the first file — orphaning it as an issue-level attachment — then aborted before posting the comment, and a retry duplicated it. Extract the URL-filter + workdir-guard + read step `issue create` already used into a shared collectLocalAttachments helper and have comment add use it: every attachment is validated and read up front, and nothing is uploaded unless all pass. Adds a command-level test asserting a valid-then-external attachment pair aborts with ZERO upload requests and no comment (fails against the old interleaved loop). Co-authored-by: multica-agent <github@multica.ai> --------- Co-authored-by: J <j@multica.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.
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-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.
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.

