623d29f276
* docs(agents): three-phase agent quick-create plan
Captures the full design for moving agent creation from manual form +
one-by-one skill attachment to a tiered experience:
- Phase 1 (this PR): one-click curated templates, AI-free.
- Phase 2 (next): AI-recommended skills via the existing quick-create
task mechanism — no new server-side LLM dependency.
- Phase 3 (later): AI creates the whole agent end-to-end, composing
Phase 2 with a new `multica agent create` CLI driver.
Documents the architectural decisions that keep all three phases on
existing infrastructure (no SSE, no server-side LLM SDK, no new WS
channels), the two soft blockers Phase 1 unlocks for later phases
(createSkillWithFiles TX composability + skill same-name dedupe), and
the scope decisions we explicitly opted out of (Anthropic plugin
marketplace, ClawHub UI affordances).
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(skills): harden import against invalid UTF-8 and binary files
PG rejects two byte patterns in a TEXT column. Both crashed real skill
imports we hit while assembling the template catalog:
- Embedded NUL (0x00) -> SQLSTATE 22021. Already stripped by
sanitizeNullBytes, kept as-is.
- Other invalid UTF-8 (e.g. 0x91 — Windows-1252 smart quote in a skill
whose author saved prose from Word). sanitizeNullBytes now also runs
strings.ToValidUTF8 over the content so the second class no longer
takes the whole import down.
For non-text payloads (images, fonts, archives, compiled binaries),
sanitization isn't the right fix — agents never read those as text,
and the bytes can't survive a TEXT column at all. addFile now skips
them by extension before the per-bundle cap counters tick, logging
the skip so an unexpected drop leaves a breadcrumb.
Function name kept for compatibility with the many call sites; both
behaviours are strict supersets of the original.
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* refactor(skills): split createSkillWithFiles for tx composition + add workspace find-or-create query
Two soft blockers cleared so create-from-template (next commit) can
fold N skill creates and the agent + binding writes into one outer
transaction:
1. createSkillWithFiles used to Begin/Commit its own tx. Caller
composition was impossible — N invocations meant N separate
transactions and no atomicity over the whole materialise step.
Pull the body into createSkillWithFilesInTx(ctx, qtx, input); the
original function becomes a thin wrapper that manages its own tx
for standalone callers. Existing call sites: zero behaviour change.
2. Add GetSkillByWorkspaceAndName sqlc query — workspace skill lookup
by name, anchored to UNIQUE(workspace_id, name) from migration
008. Lets the template materialiser implement find-or-create:
reuse the workspace's existing skill row when a template
references the same name, rather than crashing on the unique
constraint or polluting the workspace with `<name>-2` clones.
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(agents): agent template catalog + create-from-template endpoint
Server-side foundation for Phase 1 of the quick-create roadmap (see
docs/agent-quick-create-plan.md). Adds:
- server/internal/agenttmpl/ — embed-loaded catalog of curated agent
templates. Each template ships pre-written instructions plus a list
of skill URLs that get materialised into the workspace at create
time. Validation runs at startup (init() panics on a malformed
template) so a bad JSON ships as a deploy-time defect, not a
runtime 500. Slug must equal the filename basename so the URL
router is mirror-symmetric with the file layout.
- 11 starter templates covering Engineering / Writing / Building /
Testing (code-reviewer, frontend-builder, planner, docs-writer,
one-pager, html-slides, full-stack-engineer, …).
- Three new endpoints, all behind RequireWorkspaceMember:
GET /api/agent-templates — picker list (no instructions)
GET /api/agent-templates/:slug — detail with instructions
POST /api/agents/from-template — materialise + create
Create flow:
1. Auth + runtime authorization happen BEFORE the GitHub fan-out
so a 403 never wastes 20s of upstream fetches.
2. Pre-flight dedupe by cached_name reuses workspace skills
without an HTTP fetch — second create-from-the-same-template
drops from 20s to <100ms.
3. Parallel fetch (30s per-URL timeout) for the remaining skills.
4. Single transaction: every skill insert, the agent insert, and
the agent_skill bindings. On any upstream fetch failure the TX
rolls back and the API returns 422 with `failed_urls` so the
UI can name the bad source(s).
5. extra_skill_ids (user-supplied additions) are verified through
GetSkillInWorkspace per id before attach, so a malicious client
can't graft a skill from another workspace via UUID guessing.
- multica agent create --from-template <slug> CLI flag dispatches to
the new endpoint with a 60s ceiling, matching `multica skill import`.
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(agents): one-click create-from-template UI
Frontend half of Phase 1. CreateAgentDialog becomes a state machine
spanning four steps:
chooser → Start blank / From template cards
blank-form → existing manual form (post-chooser)
duplicate-form → existing form pre-filled from a duplicated agent
template-picker → grid of templates, click navigates to detail
template-detail → instructions + skill list preview + one-click Use
Picking a template never lands on the form: name auto-deduped against
existingAgentNames, runtime = first usable one, visibility = private.
Refinement happens on the agent detail page if needed. Same rationale
the doc spells out — templates exist precisely to skip configuration.
New components, all collapsible-by-default so quick-create stays fast:
- template-picker.tsx — categorised grid, lucide icons + semantic
accent tokens resolved through static maps so Tailwind's JIT picks
up every variant (dynamic class strings would silently miss).
- template-detail.tsx — instructions preview, skill list with cached
descriptions, Use CTA. Renders the failedURLs banner when a 422
fires — the only step that can trigger that response.
- instructions-editor.tsx — collapsed preview-card / expanded full
ContentEditor.
- skill-multi-select.tsx + skill-picker-list.tsx — shared multi-
select surface, also adopted by the existing skill-add-dialog.
- avatar-picker.tsx — agent avatar upload, mirrors the inspector's
visual language.
Schema-defended client (CLAUDE.md → API Response Compatibility): the
three new endpoints are wired through parseWithFallback with lenient
zod schemas. Desktop builds outlive any given server — a future
field rename / wrapping must not white-screen older installs.
listAgentTemplates accepts both the current bare array and a future
{templates: [...]} envelope. Coverage: 7 new schema-test cases in
schema.test.ts (null body, missing skills/instructions, malformed
create response, envelope migration).
Catalog + detail go through TanStack Query with staleTime: Infinity —
workspace-independent static data, no per-mount refetch.
Other:
- skill-add-dialog becomes a true multi-select (Confirm button +
checkbox list); attached skills are filtered out of the list.
- agents-page hands the freshly-created Agent back to the dialog so a
follow-up setAgentSkills can attach the form-selected skills.
- agent-overview-pane drops the mx-auto/max-w-2xl frame on config-
tab content; the wider dialog visual language reads better with
tabs filling the column.
- Every new UI string lives in both en/agents.json and
zh-Hans/agents.json under create_dialog.* / tab_body.skills.* —
locales/parity.test.ts blocks drift in CI.
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(ci): align skill import test + drop next-only lint suppression
- TestFetchFromSkillsSh_ResolvesRootLevelSkillMd now expects assets/logo.png
to be skipped; matches the new addFile binary-extension guard
(6fafd86e). The .png is intentionally dropped so PG TEXT inserts don't
hit SQLSTATE 22021.
- packages/views shares zero next/* deps, so the @next/next/no-img-element
eslint plugin isn't loaded there. The eslint-disable directive
referencing it produced a hard "rule not found" error in CI lint. Raw
<img> is the right primitive in views; remove the disable comment.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: multica-agent <github@multica.ai>
* test(agents): wrap CreateAgentDialog tests in workspace/navigation providers
The dialog now calls useNavigation() and useWorkspacePaths(), both of
which throw outside their providers. The existing tests rendered the
dialog bare and tripped both new requirements:
- NavigationProvider — supply a stub adapter so push() works for the
agent-detail redirect.
- WorkspaceSlugProvider — useWorkspacePaths() requires a slug.
The blank-vs-template chooser is now the default first step; the
existing tests target the runtime picker on the manual form, so the
helper auto-clicks "Start blank" when no template is passed
(duplicate-mode tests skip the chooser).
Manual afterEach(cleanup) + document.body wipe. Base UI's Dialog
portal renders into document.body and leaves focus-guard/inert wrapper
divs behind across tests, so the second test in the suite saw two
"All" / "My Runtime" matches and getByText failed. The wipe is local
to this file rather than the shared setup because it isn't a global
issue — only suites that open Base UI dialogs hit it.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: multica-agent <github@multica.ai>
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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.
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.
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.