21cd617d16
Stage 3 of the Composio epic. Wires the per-user Composio MCP session into
every agent task so the agent process sees the initiator's connected tools
without any prompt-time plumbing.
Server side
- Migration 128 adds agent_task_queue.runtime_mcp_overlay JSONB plus a
BEFORE-UPDATE trigger that wipes the column on any transition into a
terminal status (completed / failed / cancelled). A trigger is the single
source of truth — future queries that flip status cannot bypass it.
- composio.Service.BuildTaskOverlay(userID) reuses CreateMCPSession and
emits the Claude-style { mcpServers: { composio: { type: http, url,
headers } } } shape the daemon's existing sidecar generators consume.
Returns (nil, nil) on zero active connections so we never burn a
Composio session for a user with nothing to call.
- TaskService grows a Composio ComposioOverlayBuilder seam, wired in
router.go after composiointeg.NewService succeeds. Five enqueue paths
(issue / mention / quick-create / chat / auto-retry) attach the overlay
after CreateAgentTask returns and before the daemon is notified — so
every claim reads a settled row, with no second daemon hop. Best-effort:
a builder failure logs and proceeds with no overlay.
- resolveInitiatorFromTriggerComment derives the initiator user from the
trigger comment when it was authored by a member. Agent-authored
triggers are not treated as initiators (their connected-apps view is
empty by construction).
Daemon side
- handler/daemon.go claim path merges task.runtime_mcp_overlay onto
agent.mcp_config via mergeMCPOverlay before populating
TaskAgentData.McpConfig. Overlay wins on server-name collisions
because it carries the live user-scoped session URL. Errors fall back
to the agent config unchanged — a bad overlay must not surprise-disable
saved MCP tools. The existing execenv sidecar generators (cursor /
codex / openclaw / opencode / hermes-kiro) need no changes: they keep
consuming the merged result through TaskAgentData.McpConfig.
Tests
- 9 merge cases (mcp_overlay_test): both-nil short-circuit, agent-only
pass-through, overlay-only canonicalization, two-side merge, name
collision (overlay wins), top-level key preservation, malformed agent
fallback, malformed overlay fallback, non-object server rejection.
- 4 dispatch cases (composio): zero-connections returns nil without
CreateSession, happy-path emits the right shape with the right user
id, empty-URL defensive branch, SDK error surfacing.
- 4 TaskService helper cases: nil Composio is a no-op (Queries-safe),
invalid initiator does not call the builder, nil overlay skips the
UPDATE, builder error swallowed without panic.
- Migration 128 verified to roll up + down + up cleanly against the test
database.
Out of scope (deferred): assignment-triggered enqueue paths with no
trigger comment get no overlay attached today (no initiator UUID flows
through enqueueIssueTask in that case). Retry paths recompute the overlay
fresh from the parent's initiator_user_id instead of inheriting the bearer
from the parent row, so a stale token can never resurface on a retry.
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, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, Kiro CLI, and Qoder 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, copilot, openclaw, opencode, hermes, gemini, pi, cursor-agent, kimi, kiro-cli, agy, qodercli) 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, Antigravity, or Qoder 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, GitHub Copilot CLI,
OpenCode, OpenClaw, Hermes, Gemini,
Pi, Cursor Agent, Kimi, Kiro CLI, Qoder 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, Kiro CLI, or Qoder 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.