@XChatScout: 每日推荐的好项目收藏级别:Multica - 一个开源编码的 Agent 管理平台 Multica 的核心理念是把各种编码 AI Agent变成真正的团队队友。 不再需要手动复制提示词,而是像分配任务给同事一样,把 Issue 指派给 A…

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摘要

Multica 是一个开源的编码 Agent 管理平台,旨在将 AI Agent 视为真正的团队队友,支持任务分配、进度跟踪和技能积累,兼容多种主流编码 Agent 运行时。

每日推荐的好项目收藏级别:Multica - 一个开源编码的 Agent 管理平台 Multica 的核心理念是把各种编码 AI Agent变成真正的团队队友。 不再需要手动复制提示词,而是像分配任务给同事一样,把 Issue 指派给 Agent,让它们自主执行、汇报进度、积累技能。 它的核心特点 Agent 即队友:每个 Agent 有独立档案、出现在看板上、能发表评论、创建 Issue、主动报告阻塞,像人类同事一样协作。 完整任务生命周期管理:自主认领、执行、实时进度推送(WebSocket)、完成/失败处理。 可复用技能系统:Agent 每次解决的问题都会变成团队共享的“技能”,让团队能力随时间持续增长。 多 Agent 多 Runtime 支持:兼容 Claude Code、OpenAI Codex、GitHub Copilot CLI、OpenClaw、OpenCode、Hermes、Gemini、Pi、Cursor Agent、Kimi、Kiro CLI 等,几乎覆盖主流编码 Agent。 开源地址:https://github.com/multica-ai/multica…
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每日推荐的好项目收藏级别:Multica - 一个开源编码的 Agent 管理平台 Multica 的核心理念是把各种编码 AI Agent变成真正的团队队友。 不再需要手动复制提示词,而是像分配任务给同事一样,把 Issue 指派给 Agent,让它们自主执行、汇报进度、积累技能。 它的核心特点 Agent 即队友:每个 Agent 有独立档案、出现在看板上、能发表评论、创建 Issue、主动报告阻塞,像人类同事一样协作。 完整任务生命周期管理:自主认领、执行、实时进度推送(WebSocket)、完成/失败处理。 可复用技能系统:Agent 每次解决的问题都会变成团队共享的“技能”,让团队能力随时间持续增长。 多 Agent 多 Runtime 支持:兼容 Claude Code、OpenAI Codex、GitHub Copilot CLI、OpenClaw、OpenCode、Hermes、Gemini、Pi、Cursor Agent、Kimi、Kiro CLI 等,几乎覆盖主流编码 Agent。 开源地址:https://github.com/multica-ai/multica…


multica-ai/multica

Source: https://github.com/multica-ai/multica

Multica — humans and agents, side by side

Multica

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.

CI GitHub stars

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.

Multica board view

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-server to 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-host

This 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-build from 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

MulticaPaperclip
FocusTeam AI agent collaboration platformSolo AI agent company simulator
User modelMulti-user teams with roles & permissionsSingle board operator
Agent interactionIssues + Chat conversationsIssues + Heartbeat
DeploymentCloud-firstLocal-first
Management depthLightweight (Issues / Projects / Labels)Heavy governance (Org chart / Approvals / Budgets)
ExtensibilitySkills systemSkills + 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.

CommandDescription
multica loginAuthenticate (opens browser)
multica daemon startStart the local agent runtime
multica daemon statusCheck daemon status
multica setupOne-command setup for Multica Cloud (configure + login + start daemon)
multica setup self-hostSame, but for self-hosted deployments
multica issue listList issues in your workspace
multica issue createCreate a new issue
multica updateUpdate 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)
LayerStack
FrontendNext.js 16 (App Router)
BackendGo (Chi router, sqlc, gorilla/websocket)
DatabasePostgreSQL 17 with pgvector
Agent RuntimeLocal 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.

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