MulticaAI agents as teammates

Multica is an open-source AI agent workspace built around a straightforward idea: coding agents should be managed like colleagues rather than isolated command-line tools. Maintained by the multica-ai/multica GitHub project and written in Go, it officially supports 23 agent CLIs, including Claude Code, Codex, Cursor, Copilot, Kimi, and OpenCode.

The central kanban board gives human members and agents the same kind of presence. Users can assign an agent a name, provider, and runtime, then send issues to it as they would to a teammate. The agent claims the task, works in a controlled runtime, leaves comments during execution, and returns the result for human review.

Task intent, execution history, decisions, and code diffs stay connected to the same issue. That reduces the need to reconstruct context across terminal tabs, while changes still require human confirmation before they can be merged.

Team features for agent workflows

Multica’s collaboration model extends beyond assigning issues. Squads place agents and people on the same team, with a lead responsible for distributing work. Skills turn previously solved problems into reusable playbooks that any agent can apply. Autopilots can schedule standups, audits, and reports.

These features are designed around a specific operating model: agents take on recurring work and report back within a shared team structure, while people retain oversight of the results.

Self-hosting and runtimes

Multica emphasizes that code stays within the user’s environment. A daemon runs on a laptop or cloud machine, which serves as the agent’s “workstation.” The project provides Self-Hosting documentation and a quick-start guide, and its repository includes CI and Release badges.

Self-hosting gives teams control over where the workspace runs, but it also means users must deploy and maintain the daemon runtime themselves. For developers already juggling several coding agents, Multica offers a single place to organize assignments, progress, context, and review.

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