multica-ai/multica

Make humans and AI agents work as one team — open-source and self-hostable.

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Summary Information

Updated 4 minutes ago
Added to GitGenius on April 12th, 2026
Created on January 13th, 2026
Open Issues & Pull Requests: 1,858 (+0)
GitHub issues: Enabled
Number of forks: 6,833
Total Stargazers: 52,449 (+3)
Total Subscribers: 184 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 11.3 hours
Mean response time: 5.8 days
90th percentile: 15.7 days
Tracked items: 2,283

Maintainer activity

9 people did triage or write work on this repository in the last 12 months.

Counts unlabeled, assigned, unassigned, milestoned, demilestoned, locked, unlocked over the last 12 months. These are issue and pull request events that require triage or write permission. Commits and code review are not counted. labeled and renamed are excluded because GitHub issue forms record the issue author as the actor. Figures from October 11, 2026. This count is not comparable across projects: each project's automation decides which of these events a person emits.

How this project is maintained

About 18% of issues opened in the past year have never received a reply. 98% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 36% of tracked open issues have had no activity in three months. 64% of issues opened in the past year have been closed, leaving a working backlog. Three people close 80% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 1,015
New in 7 days: 60
Closed in 7 days: 18
Avg open age: 12 days
Stale 30+ days: 769
Stale 90+ days: 364

Recent activity

Opened in 7 days: 53
Closed in 7 days: 17
Comments in 7 days: 35
Events in 7 days: 73

Top labels

  • enhancement (674)
  • bug (580)
  • question (23)
  • good first issue (12)
  • documentation (7)
  • duplicate (1)
  • help wanted (1)
  • needs-info (1)

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Detailed Description

Multica is an open-source workspace that assigns coding tasks to AI agents like Claude Code, Codex, Cursor, and others as if they were teammates.

The tool solves the fragmentation problem of managing multiple AI coding agents across separate terminal sessions and contexts. Instead of juggling different agents in isolation, each losing context between sessions, Multica centralizes them in a shared workspace. When you assign an issue to an agent, it picks up the work autonomously, executes code on a runtime you control, reports progress through comments, and submits results for human review. The intent, execution, decisions, and resulting diff all stay connected to the same issue, eliminating the need to repeatedly explain context or reconstruct what happened.

Multica suits teams that want to leverage multiple coding agents without vendor lock-in or the overhead of managing each one separately. It works with twenty different agent CLIs, so you can use Claude Code, Codex, Cursor, Copilot, Kimi, and others together rather than choosing one. The tool supports organizing agents into squads with human teammates, creating reusable skills from solved problems, and running automated workflows like standups and audits on a schedule. You can self-host it on your own infrastructure, keeping code execution on machines you control, or use the cloud version. The workspace includes chat for ad-hoc questions and projects for grouping related work with attached repositories and documentation.

The project shows strong adoption signals: almost all open issues come from external users rather than the core team, indicating a substantial base of real-world users. Maintainers respond to new issues and pull requests within a day. Work in the issue tracker centers on bug reports, enhancement requests, and user questions, reflecting active engagement with the community.