paca

What is Paca?

Paca is a self-hosted project management platform where AI agents and humans collaborate as equal teammates inside a Scrum team — not as chatbots bolted on the side.

Jira gives you a backlog. ClickUp gives you automations. Monday gives you dashboards. Paca gives your AI agents a seat at the table. They join sprint planning, pick up tasks from the board, write BDD specs, and adapt alongside humans in real time.

Everything about Paca — its workflow, its data model, its UI — is configurable and extendable via plugins.

Why Paca?

Core Idea: Humans and AI Agents, One Scrum Team

The central insight behind Paca is that AI agents should participate in the Scrum process, not just generate output in isolation.

In Paca, AI agents:

• Are assigned to sprints and appear on the Scrumban board alongside human teammates
• Pick up tasks from the backlog and update their status in real time
• Collaborate on BDD specs — helping Product Owners and BAs write Gherkin scenarios
• Contribute to System Design Documents — keeping the architecture visible to the whole team
• Probe, sense, and respond to emerging complexity, just like a human would

This is not automation. It is genuine collaboration — rooted in the Cynefin / Stacey framework's recognition that complex domains require teams, not pipelines.

Fully Customizable — Configuration and Plugins

Paca ships as a small, focused core. Everything else is optional.

Configuration-driven: workflows, statuses, field definitions, board layouts, sprint rules, and agent behavior are all driven by project-level configuration files. No code needed to adapt Paca to your team's process.

Plugin system: extend or replace any part of Paca via plugins. Plugins are compiled to WebAssembly (WASM) for the backend (write in Go, Rust, AssemblyScript — anything with a WASM target) and standard module bundles for the frontend. Plugins run in a sandboxed environment with a capability-based permission model; they declare exactly what host functions they need, and nothing more.

plugins/
├── backend/        # WASM modules — add custom routes, logic, data models
└── frontend/       # UI modules — add custom pages, board views, widgets

Browse and install community plugins directly from the Plugin Marketplace inside the Paca UI — no command line required. Go to Settings → Plugins → Marketplace, find a plugin, and click Install.

For local development or custom plugins, you can also install from the filesystem:

./scripts/install-local-plugin.sh ./my-plugin --api-key <your-api-key>

The P-A-C-A Cycle

Paca structures team collaboration around four phases that mirror both Scrum and the scientific method:

Plan  →  Act  →  Check  →  Adapt
  ↑                             |
  └─────────────────────────────┘

What's New in v0.17.0

• Jev AI integration — plug Jev, an AI decision engine, into any project to let it make the small routing calls a team makes all day. It's opt-in and per-project: bring your own key for TypeSafe (the default) or any Jev-compatible provider such as OpenJev from Settings → Jev AI. The key is encrypted at rest and never shown again, and a project without a key behaves exactly as before.
  • Agent Auto-routing — pick Auto in the chat's agent picker and Jev hands your message to the best-fit agent, based on each agent's description.
  • Task Auto-fill — when a task is created, Jev fills in the fields left blank (priority, type, story points, tags, epic, and select/boolean custom fields). It only applies confident answers and never overwrites a field a person set.
  • Task Auto-assign — set a task's assignee to Auto and Jev picks the best-matching member from their descriptions. If it isn't confident, it leaves the task unassigned and says why in the activity feed.
  • Jev Condition in automations — a new condition node that routes a workflow on Jev's answer (a choice, a score, or yes/no), falling back to the Else branch whenever Jev is unsure or unavailable.

What's New in v0.15.0

• Browser extension for page annotations — comment directly on an element of a running environment's preview page, right on the page itself, and turn any comment into a real Paca task in one click. It authenticates through your existing Paca session — no separate login — via the same-hostname cookie trick documented in apps/extension/README.md. Install the pre-built zip from each release, or build it from source.

• provider_cli agent type — run an agent on a CLI you're already logged into — Claude Code, Codex, Gemini CLI, or Cursor CLI — inside one of its own static environments. Log into the CLI once from the environment's terminal (a static environment, because the CLI's own login has to persist across conversations), and Paca drives that CLI directly for every conversation afterward, syncing your configured MCP servers into its config along the way.

What's New in v0.14.0

• Static environments — create a named, long-lived container that persists independently of any single conversation: agents attach to it instead of spinning up a fresh disposable sandbox, so files on disk and background processes survive across chats. Reach a running environment through an in-browser terminal, real SSH with per-environment authorized keys, or user-managed port forwards to preview a live dev server — on both self-hosted Docker Compose and Kubernetes/Helm. See docs/ai-agent/environment-management.md for the full design.