131ca80a6c
* refactor(autopilot): migrate scheduled dispatch to scheduler.Manager
PR 3 of 3 for the scheduled-Autopilot refactor on MUL-3551.
Replaces the legacy cmd/server/autopilot_scheduler.go goroutine
(30 s app-clock polling, app-time cron advancement, weak crash
recovery) with a JobSpec registered on the existing
scheduler.Manager. sys_cron_executions is now the lease + audit
table for scheduled Autopilot occurrences, and the unique key on
(job_name, scope_kind, scope_id, plan_time) is the primary
guarantee that the same planned fire time cannot produce two runs.
What changed
* server/internal/scheduler/jobs_autopilot.go
New AutopilotScheduleDispatchJob factory:
- scope_kind = "autopilot_trigger", scope_id = trigger.id
- PlansForScope hook (from PR 1) enumerates cron occurrences
in (lastPlan, dbNow] and collapses missed fires to the most
recent one (CatchUpLatestOnly — same policy the legacy
goroutine had, now provable via a one-row-per-tick audit).
- Handler re-loads trigger + autopilot inside the handler so a
between-tick state change (paused, disabled, deleted) takes
effect immediately and is recorded as a no-op SUCCESS row
with skipped_reason in the result JSON.
- Calls AutopilotService.DispatchAutopilotForPlan (from PR 2)
for the actual run creation; that path is itself idempotent
on (trigger_id, planned_at), so a stale-steal retry reuses
the run created by the prior attempt instead of duplicating.
- RunTimeout=2m, StaleTimeout=5m, HeartbeatInterval=30s,
AllowStaleReentry=true, MaxAttempts=3, RetryBackoff
[1m, 5m, 15m], MaxPlansPerTick=5 (safety cap).
* server/internal/scheduler/manager.go
Manager.runOnce promoted to RunOnce (exported) so external test
packages can drive deterministic ticks; existing call sites in
this package + cmd/server tests updated.
* server/internal/service/cron.go
NextOccurrenceAfterUTC and NextOccurrencesUTC: cron evaluators
that take an explicit "now" instant. Callers pass dbNow() so
schedule decisions stay consistent across app instances with
clock skew. Legacy ComputeNextRun is preserved (delegating to
NextOccurrenceAfterUTC with time.Now()) for the display-only
autopilot_trigger.next_run_at write path — scheduling decisions
no longer use it.
* server/pkg/db/queries/autopilot.sql
ListSchedulableAutopilotTriggers replaces the legacy
ClaimDueScheduleTriggers (the new path no longer mutates
autopilot_trigger.next_run_at on claim). RecoverLostTriggers
removed — sys_cron_executions lease theft now handles crash
recovery without an in-handler restart sweep.
* server/cmd/server/main.go
The "go runAutopilotScheduler(...)" line is gone. The new
JobSpec is registered alongside TaskUsageHourlyJob on the
existing schedulerMgr (still using sweepCtx for lifecycle).
* server/cmd/server/autopilot_scheduler.go DELETED.
Tests
* server/internal/service/cron_test.go — unit tests for the cron
helpers: timezone-aware enumeration, half-open (after, until]
window, plan_time-exclusive "after", invalid inputs surface
parse errors, and the "ignores wall clock" property the
scheduler relies on.
* server/cmd/server/autopilot_schedule_job_test.go — DB-backed
integration tests:
- DispatchesOnce: one tick → 1 SUCCESS exec row + 1
autopilot_run with planned_at set; a second tick does not
regress the count.
- MissedSchedulesCollapse: an hour of missed */5 fires
produce a single autopilot_run, not 12.
- CrashRecovery: simulated stale RUNNING lease at the same
plan_time → second tick reclaims it and DOES NOT duplicate
autopilot_run.
- TwoRunnersSingleWinner: two concurrent
scheduler.Manager instances on the same trigger →
per-plan_time uniqueness holds (sys_cron_executions never
has two RUNNING rows at the same plan_time, autopilot_run
count == exec row count).
- DisabledTriggerSkips: a trigger disabled between
scope-list and tick produces no exec row.
- PausedAutopilotSkipsAtHandler: an autopilot paused after
the first tick does not produce a new exec row.
- BadCronFailsLoudly: an invalid cron expression never fires
dispatch (parse error surfaces in the plan hook).
Existing autopilot listener / squad / dispatch tests still
pass.
* server/internal/scheduler/plans_for_scope_test.go from PR 1
still passes (RunOnce rename only).
Verification
* go build ./...
* go vet ./...
* go test ./internal/scheduler ./internal/service ./cmd/server
./internal/handler — all green.
Rollback
* Reverting this commit re-introduces the legacy goroutine.
Migration 124 (PR 2) and the scheduler hook (PR 1) stay in
place. Autopilot data on disk is forward- and backward-
compatible: planned_at columns are nullable, the legacy
goroutine never reads planned_at and the new job never reads
autopilot_trigger.next_run_at.
Refs MUL-3551
Co-authored-by: multica-agent <github@multica.ai>
* fix(autopilot): scheduler hook retries FAILED plans + tighten tests
Review fix for #4444 (MUL-3551).
Blocker: hook planner skipped the FAILED-with-retry plan_time
`autopilotPlansForScope` unconditionally set
`after = latest.PlanTime` when `latest.Found`, then enumerated cron
occurrences in the half-open interval `(after, dbNow]`. That
EXCLUDED the FAILED plan_time itself, so `tryClaim`'s
"FAILED-with-retry" branch — which only fires when the planner
returns the same plan_time — never ran. A claim + crash sequence
left the FAILED row stuck at attempt<max_attempts forever and the
scheduled occurrence was lost (MUL-3551 acceptance ③).
Fix: hook now branches on `latest.RetryEligible(now)` BEFORE
computing `after`. When the most recent stored row is FAILED with
attempts remaining and next_retry_at <= dbNow, the hook returns
`[latest.PlanTime]` unchanged. tryClaim's retry-from-FAILED path
fires, attempt increments, the run is retried, and the audit row
reaches SUCCESS at the same plan_time. Mirrors the cadence
planner's `info.RetryEligible(now)` branch in manager.plansForTick.
Tests
* TestAutopilotScheduleJobCrashRecovery rewritten to actually
pin the retry contract instead of just "no duplicate run":
- assert first attempt completes at attempt=1 with a real
task_id linkage (the "complete" snapshot the retry must
reuse);
- simulate a crash mid-dispatch (status=RUNNING, expired
stale_after, ghost lease_token);
- assert tick 2 transitions the SAME exec row (same plan_time)
to status=SUCCESS at attempt=2 (proving the planner did
NOT skip past the FAILED bucket);
- assert autopilot_run stays at exactly one row, reused from
the first attempt — proving DispatchAutopilotForPlan's
complete-run reuse path is what closes the loop.
* TestAutopilotScheduleJobPausedAutopilotSkipsAtHandler rewritten
to invoke `job.Handler` directly (the previous version drove
`mgr.RunOnce` which short-circuited at the scope-list SQL
filter and never reached the handler). The new test pauses the
autopilot AFTER setup, calls the handler with a fabricated
HandlerInput, and asserts the handler returns
skipped_reason=autopilot_inactive without creating an
autopilot_run.
* TestAutopilotScheduleJobBadCronFailsLoudly renamed to
TestAutopilotScheduleJobBadCronStaysSilent and updated to
match the real implementation: a parse error in the plan hook
surfaces as a manager-level warning log, NOT a
sys_cron_executions row (no plan_time was ever claimed). The
test now asserts zero exec rows AND zero autopilot_run rows,
documenting that bad cron is a permanent configuration error
(caught at HTTP create/update time first), not a transient
failure that belongs in the retry envelope.
Refs MUL-3551
Co-authored-by: multica-agent <github@multica.ai>
---------
Co-authored-by: Eve <eve@multica-ai.local>
Co-authored-by: multica-agent <github@multica.ai>
Multica
Your next 10 hires won't be human.
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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.