eb067ff077
* fix(server): aggregate task_usage into daily rollup table to cut DB load ListRuntimeUsage previously did a SUM(...) GROUP BY DATE(created_at), provider, model over the raw task_usage stream once per runtime row on the runtimes list and once per detail page load, scaling O(events) per call. This is the hot read path responsible for sustained load on Postgres. Switch the read path to a materialized daily rollup table maintained by a pg_cron job: - 072_task_usage_daily_rollup: schema for task_usage_daily + task_usage_rollup_state, plus rollup_task_usage_daily_window(p_from, p_to) (window primitive used by both cron and offline backfill, idempotent via ON CONFLICT DO UPDATE adding deltas) and rollup_task_usage_daily() (cron entry point — pg_try_advisory_lock(4242) for serialization, watermark advancement, 5-minute safety lag for late-visible inserts). Also adds idx_task_usage_created_at to help the two lazy endpoints (ListRuntimeUsageByAgent / GetRuntimeUsageByHour) that still hit the raw table. - 073_task_usage_daily_pgcron: CREATE EXTENSION IF NOT EXISTS pg_cron in a DO/EXCEPTION block (mirrors the migration 032 pg_bigm pattern so envs without shared_preload_libraries=pg_cron skip gracefully) and schedules rollup_task_usage_daily() every 5 minutes when the extension is present. - queries/runtime_usage.sql ListRuntimeUsage rewritten to read from task_usage_daily; sqlc regenerated. Other usage queries unchanged. - cmd/backfill_task_usage_daily: one-shot Go command that walks task_usage in monthly slices through rollup_task_usage_daily_window, then stamps the watermark to now()-5m so the cron resumes cleanly. Run once after migrations have applied, before relying on the rollup. - runtime_test.go: TestGetRuntimeUsage_BucketsByUsageTime now invokes rollup_task_usage_daily_window after fixture inserts so the handler sees the rolled-up rows. Synthetic daily rows cleaned up after each test. - runtime_rollup_test.go: new tests covering aggregation correctness, idempotency contract of ON CONFLICT DO UPDATE, and the watermark advancing exactly to now()-5m via the cron entry point. Deployment order: apply migrations → run backfill_task_usage_daily once → pg_cron picks up subsequent windows automatically. Today bucket may be up to ~10 minutes stale (5 min cron + 5 min lag) by design. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: multica-agent <github@multica.ai> * fix(server): make task_usage_daily rollup safe to overlap, replay, and correct Addresses 4 review blockers on the original PR: 1. Cron/backfill double-count race: the rollup function is now idempotent. Window calls find DIRTY KEYS via task_usage.updated_at, then RECOMPUTE each bucket from ground truth and REPLACE the daily row (no more additive ON CONFLICT). Cron and backfill can now overlap safely. 2. Silent pg_cron absence: the read path is gated behind a new USAGE_DAILY_ROLLUP_ENABLED feature flag (default off). The raw task_usage scan is preserved as the fallback. Operators flip the flag per-environment after backfill + cron are confirmed healthy (task_usage_rollup_lag_seconds() helper added for monitoring). 3. UpsertTaskUsage corrections invisible to rollup: added task_usage.updated_at column (default now(), backfilled from created_at), and bumped it on conflict. Corrections now mark the bucket dirty and the next window call recomputes it correctly. 4. CREATE INDEX blocking writes on hot table: split into separate single-statement migrations using CREATE INDEX CONCURRENTLY (074, 075), matching the 035/067 pattern. Also: cron.schedule() removed from migrations entirely. Migration 076 only enables the extension (gracefully on unsupported envs); the actual schedule is a documented operator runbook step that runs AFTER backfill. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: multica-agent <github@multica.ai> * fix(server): trigger-driven invalidation + online-safe migration for task_usage_daily Round-2 review feedback on PR #2256: 1. Add explicit dirty-bucket queue (task_usage_daily_dirty) populated by triggers on agent_task_queue (UPDATE OF runtime_id, DELETE) and task_usage (DELETE). The rollup window function drains both this queue and the updated_at-based discovery, so runtime reassignment and issue-cascade deletes no longer leave the rollup divergent from the raw query. Triggers join via agent (not issue) to look up workspace_id, because when the cascade comes from issue, the issue row is already gone by the time atq's BEFORE DELETE fires; agent stays alive. 2. Make migration 072 online-safe: only ADD COLUMN updated_at TIMESTAMPTZ (nullable, no default → metadata-only ALTER, no row rewrite) and a separate ALTER for SET DEFAULT now() (also metadata-only). No bulk UPDATE on the hot task_usage table. The rollup window function's dirty_keys CTE handles legacy NULL rows via an OR branch, supported by partial index idx_task_usage_created_at_legacy. 3. Refresh stale documentation in cmd/backfill_task_usage_daily/main.go header to describe the current recompute/replace semantics, idempotent re-runnability, and the actual migration numbering (072..077). Tests: - TestRollupTaskUsageDaily_InvalidationOnReassign: verifies usage moves between runtime buckets after ReassignTasksToRuntime-style update. - TestRollupTaskUsageDaily_InvalidationOnIssueDelete: verifies daily bucket is cleared after issue delete cascades through atq → task_usage. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: multica-agent <github@multica.ai> * fix(server): close dirty-queue race + move legacy partial index to its own concurrent migration Round-3 review feedback on PR #2256: 1. Blocker: dirty-queue invalidations could be silently lost under concurrency. ON CONFLICT DO NOTHING let a late trigger see the row already enqueued, no-op, and then the rollup drain (WHERE enqueued_at < p_to) would delete the original row — losing the late invalidation. Switched all three trigger enqueue paths to ON CONFLICT DO UPDATE SET enqueued_at = GREATEST(existing, EXCLUDED.enqueued_at), so any invalidation arriving during a rollup tick keeps enqueued_at > p_to (p_to = now() - 5min) and survives the post-tick drain. 2. High: idx_task_usage_created_at_legacy (partial index on hot task_usage table) was being created in the regular 077 migration without CONCURRENTLY. Moved to new migration 078 with CREATE INDEX CONCURRENTLY, matching the pattern of 074/075. 077's down migration leaves the index alone (it is owned by 078). 3. Minor: gofmt -w on runtime_rollup_test.go and backfill_task_usage_daily/main.go (tabs were lost in the original heredoc append). PR description rewritten to describe the current recompute/replace + dirty queue + feature flag design and the 072..078 migration ordering. Tests still green: TestRollupTaskUsageDaily_* (including both new invalidation regressions), TestGetRuntimeUsage_*, TestWorkspaceUsage_*. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: multica-agent <github@multica.ai> * fix(server): unify workspace_id source via agent in rollup window function Round-4 review feedback (J) on PR #2256: M1 (must-fix): The dirty queue triggers resolved workspace_id via `agent.workspace_id`, but the window function's `dirty_from_updates` discovery and `recomputed` recompute join used `issue.workspace_id`. There is no schema-level FK guaranteeing `agent.workspace_id == issue.workspace_id`. Any divergence (future cross-workspace task scenarios, data repairs, migration bugs) would cause: - dirty queue rows with workspace_id from agent - recompute join filtering by workspace_id from issue - 0 matches in recompute → bucket erroneously hits the deleted_empty branch and the daily row is silently dropped - dirty_from_updates path attributing usage to the wrong workspace Replaced both CTEs to JOIN agent (not issue) so trigger / discovery / recompute share one workspace_id source. Comment in 077 explains the constraint. N1: Refreshed two stale references in cmd/backfill_task_usage_daily/main.go (header now says "072..078"; stampWatermark warning now mentions migration 073, where the rollup state table is actually introduced). Test: New TestRollupTaskUsageDaily_WorkspaceMismatch constructs an atq with agent.workspace_id != issue.workspace_id, asserts the bucket lands under agent's workspace (not issue's), and re-asserts after a runtime reassign in the foreign workspace. Acts as a canary if the schema invariant changes. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: multica-agent <github@multica.ai> --------- Co-authored-by: Eve <eve@multica.ai> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: multica-agent <github@multica.ai> Co-authored-by: Devv <devv@Devvs-Mac-mini.local>
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, and Kiro CLI.
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.
- 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-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) 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, or Kiro 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.
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, 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.