multica

multica is an agent framework - Make humans and AI agents work as one team — open-source and self-hostable.

Overview

Multica is an open-source workspace where you assign work to AI coding agents the way you'd assign it to a teammate — they pick up the issue, report progress, raise blockers, and hand it back for review. Self-hostable, works with 23 agent CLIs, no lock-in.

You already run Claude Code, Codex, and three other agents. Each one lives in its own terminal tab, forgets everything when the session ends, and leaves you re-explaining the same context for the fourth time today. The more agents you add, the more of your day goes to babysitting them.

Multica puts those agents and your teammates in one workspace. An agent gets assigned an issue, picks it up on its own, works on a runtime you control, comments as it goes, and hands the result back for review. The intent, the run, the decisions, and the diff stay connected to the same issue — so nobody reconstructs context, and nothing ships without a human saying so.

Claude Code, Codex, Cursor, Kimi — you don't pick one. You hire them all.

multica is open-source, written primarily in Go, with 47,886 GitHub stars under the Other license. The latest release is v0.4.35 (2026-08-26).

Key capabilities

From the project's documentation:

• 23 agent CLIs → Claude Code, Codex, Cursor, Copilot, Kimi, OpenCode, and more.
• Squads → Put agents and people on one team; the leader routes the work.
• Skills → Turn a solved problem into a playbook every agent reuses.
• Autopilots → Run standups, audits, and reports on a cron — nobody to remind.
• Chat → Ask your workspace a question, or start work without filing anything.
• Projects → Group work and attach the repos and docs agents need as context.

Install

A quick way to get started (always check the official docs for the latest):

curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash

How it fits a local-AI stack

multica runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related agent frameworks in the directory:

• "agentic-inbox"
• Agno
• "ai-agents-from-scratch"
• "aider"

Sources

• Source code & docs: multica-ai/multica
• Official website: https://multica.ai

Stats from GitHub, 2026-08-27.