rookedsysc/kanvibe — Self-hosted Kanban board with browser terminals for AI coding agents.

Description and use

**Brief Summary (2‑3 sentences)**
Kanvibe (rookedsysc/kanvibe) is a self‑hosted Kanban board that embeds browser‑based terminals, letting AI coding agents interact with tmux/zellij sessions and git worktrees directly from the board. Its hook‑driven auto‑tracking synchronises board cards with development environments, making it easy to prototype AI‑augmented workflows without building a custom model stack.

**Value**

• **Rapid AI integration** – Developers can attach AI agents to existing terminal sessions and version‑control contexts, turning a Kanban board into an orchestrator for code‑generation, RAG pipelines, or autonomous debugging.
• **Unified view** – Tasks, terminal outputs, and git states are visualised together, reducing context‑switching and improving traceability of AI‑driven actions.
• **Low‑code entry point** – Because the platform is built in TypeScript and runs as a Docker‑compose service, teams can start experimenting without deep infra changes or model training.

**Practical Adoption Path**

1. **Proof‑of‑Concept** – Clone the repo, run the provided Docker setup, and connect a single tmux/zellij session to a test board. Verify that hooks update cards as expected.
2. **Pilot Integration** – Add a small AI agent (e.g., OpenAI function‑calling wrapper) that listens to board events and performs a simple code‑generation task. Document the workflow in the README for team onboarding.
3. **Scale Gradually** – Extend to multiple worktrees, add RAG components, and configure role‑based access. Tie CI/CD pipelines to board actions for automated testing or deployment triggers.

**Production Readiness**

• **Maturity**: Medium. The project is actively maintained (last commit 2026‑05‑14), has 122 ★ and 14 forks, and is written in TypeScript, which eases integration for modern web stacks.
• **Considerations**: Verify the open‑source license, conduct a security audit of the terminal‑exposure layer, and evaluate dependency updates (npm packages).
• **Fit for Production**: Suitable for internal tools, prototypes, or controlled environments after a short hardening phase (security review, monitoring, and CI validation). Not yet a turnkey, enterprise‑grade solution, but a solid foundation for teams that want to embed AI agents into their development workflow.

Problem

rookedsysc/kanvibe helps add AI capability without starting from a blank model stack.

Outcome

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

Self-hosted Kanban board with browser terminals for AI coding agents. Hook-driven auto-tracking — manage tmux/zellij sessions and git worktrees from one board.

Source