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MCP Servers · Paca-AI

paca

Paca is a self-hosted, open-source project management platform that treats AI agents as equal Scrum team members alongside humans. Built in Go with Apache 2.0 licensing, it offers Jira/Trello/ClickUp-like functionality with native AI collaboration, real-time boards, BDD support, and a WASM plugin system for deep customization.

Source: GitHub — github.com/Paca-AI/paca
1.5k
GitHub stars
101
Forks
Go
Primary language
Apache-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
RepositoryPaca-AI/paca
OwnerPaca-AI
Primary languageGo
LicenseApache-2.0 — OSI-approved
Stars1.5k
Forks101
Open issues5
Latest releasev0.8.0 (2026-07-03)
Last updated2026-07-07
Sourcehttps://github.com/Paca-AI/paca

What paca is

Written in Go, Paca provides a Scrumban board with real-time Socket.IO updates, in-app AI chat, MCP server integration, WASM-based plugin sandboxing (backend) and module bundles (frontend), System Design Documents, and OpenHands-powered agent containers. Self-hosted via Docker Compose; data and execution remain on-premises.

Quickstart

Get the paca source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/Paca-AI/paca.gitcd paca# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Scrum teams integrating AI agents as genuine collaborators

Paca is purpose-built for teams where AI agents participate in sprint planning, task selection, BDD scenario writing, and real-time board updates alongside human teammates—not as peripheral chatbots.

Organizations requiring self-hosted, data-sovereign project management

All data stays on your infrastructure with no cloud vendor lock-in. Compliance-sensitive teams (healthcare, finance, regulated sectors) can fully own their project data and execution environment.

Teams needing deep process customization without vendor enterprise fees

Configuration-driven workflows and a plugin marketplace allow complete adaptation of statuses, fields, board layouts, and agent behaviors. No enterprise tier paywall; all customization is available in the open-source core.

Implementation considerations

  • Installation requires Docker Compose on a Linux server; interactive install script and manual configuration templates are provided. Estimate 1–2 hours for initial deployment and DNS/TLS setup via Caddy.
  • AI agent execution runs inside isolated OpenHands sandbox containers; ensure your host has sufficient CPU and memory (baseline not specified in README; requires testing for your team size).
  • Plugin development requires Go/Rust/AssemblyScript knowledge for backend WASM modules and JavaScript for frontend UI modules. The plugin marketplace model suggests community plugins exist, but availability and quality are Unknown.
  • Configuration is project-level and file-driven (workflows, statuses, fields, sprint rules, agent behavior). Teams must define their Scrum process upfront; ad-hoc changes to the config model may require restart or reload.
  • Real-time Socket.IO updates assume stable network; mobile/offline support and conflict resolution for concurrent edits are not mentioned. Suitability for distributed teams with poor connectivity is Unknown.

When to avoid it — and what to weigh

  • You need a mature, battle-tested enterprise project tool with years of production hardening — Paca v0.8.0 is recent (launched March 2026) with only ~1.5k stars and 5 open issues. While active, it has not yet accumulated the operational maturity and migration history of Jira or Monday.com across thousands of teams.
  • Your team operates primarily without AI agent involvement — Paca's core value proposition is human–AI collaboration. If your team has no plans to adopt AI agents or prefers a lightweight task tracker, Paca's agent-centric design and plugin overhead may not justify the adoption cost.
  • You need out-of-the-box integrations with dozens of SaaS tools — Paca's integration ecosystem is not documented in the README. Custom integrations would likely require WASM plugin development; native connectors to Slack, GitHub, Salesforce, etc. are not mentioned.
  • You lack in-house DevOps capacity to self-host, patch, and maintain Docker infrastructure — Self-hosted projects require operational overhead: Docker Compose management, OS updates, backup strategy, monitoring, and upgrade coordination. Cloud-hosted SaaS (Jira Cloud, ClickUp, Monday) removes this burden.

License & commercial use

Apache License 2.0 is a permissive OSI-approved license allowing commercial use, modification, and redistribution with clear attribution and liability disclaimer. The license is well-established, widely understood, and places no restrictions on how you use Paca's code or data within your organization.

Apache 2.0 explicitly permits commercial use. You may deploy Paca in commercial settings, charge for services built on top of it, and modify the code without license restrictions. However, always include a copy of the Apache license and document changes. No commercial support contract, SLA, or legal indemnification is mentioned; commercial support would likely require a separate agreement with the Paca-AI team or a third-party provider. For mission-critical deployments, verify support availability before adopting.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityModerate
DEV.co fitStrong
Assessment confidenceMedium
Security considerations

Paca stores all project data and agent execution on your infrastructure (self-hosted). Key considerations: (1) WASM plugin sandbox uses capability-based permissions; plugins declare required host functions and cannot exceed those permissions. Verify sandbox integrity through code review or audit if deploying untrusted plugins. (2) AI agents execute in isolated OpenHands containers; ensure container runtime is updated and host is patched to prevent breakout. (3) No mention of encryption at rest, audit logging, role-based access control (RBAC), or secrets management. These should be verified in full docs or codebase before handling sensitive data. (4) JWT secrets and database passwords must be strong and rotated per your security policy. (5) Caddy TLS setup is included; verify it matches your organization's certificate and CA policies.

Alternatives to consider

Jira Cloud + Jira Automation + third-party AI plugins

Jira is battle-tested, vendor-supported, has extensive integrations, and runs in managed cloud. Trade-offs: proprietary, per-seat cost ($8–$20/month), limited AI-as-teammate model, and data on Atlassian servers. Suitable if you need enterprise maturity and don't require on-premises data sovereignty.

ClickUp or Monday.com with custom automations

Both are SaaS, feature-rich, and support AI add-ons and automation. Trade-offs: cloud-only, per-seat cost, limited customization (locked behind enterprise tiers), and no true AI-as-teammate collaboration. Suitable for teams comfortable with vendor lock-in and monthly spend.

Open-source alternatives: Taiga, Plane, or Openproject

All are open-source, self-hosted, and support customization. Taiga and Plane focus on Agile/Kanban; Openproject is heavier and more enterprise. Trade-offs: weaker or no AI integration, smaller communities, and less active development than Paca. Suitable if AI collaboration is not a priority.

Software development agency

Build on paca with DEV.co software developers

Deploy Paca on your infrastructure with one Docker command. Customize workflows, plugins, and agent behavior to match your team's process. All code is open-source; your data stays on-premises.

Talk to DEV.co

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paca FAQ

Can I use Paca without AI agents?
Yes. Paca is a full project management platform with Scrumban boards, sprint planning, BDD support, and SDD docs. However, Paca's core design assumes AI agents as participants; using it without them underutilizes the platform's intended value proposition. For human-only teams, alternatives like Plane or Taiga may be simpler.
What AI models or agents does Paca support?
Paca integrates with OpenHands-powered agents and supports MCP (Model Context Protocol) for Claude and custom agents. Specific supported LLM providers (OpenAI, Anthropic, etc.) are not detailed in the README. Review the architecture docs and configuration templates for supported agent SDKs.
How do I back up my Paca data?
Unknown. Paca uses PostgreSQL for persistence (mentioned in Docker Compose). Standard PostgreSQL backup tools (pg_dump, WAL archiving) apply, but Paca-specific backup guidance and restoration procedures are not in the README. Verify backup strategy in production docs.
Can I migrate from Jira or Monday to Paca?
Unknown. No migration tools or import procedures are mentioned. Data import would likely require custom WASM plugins or direct PostgreSQL import. Contact the Paca-AI team or community for migration guidance before committing to a switch.

Custom software development services

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If paca is part of your mcp servers roadmap, our team can implement, customize, migrate, and maintain it.

Ready to bring AI agents into your Scrum process?

Deploy Paca on your infrastructure with one Docker command. Customize workflows, plugins, and agent behavior to match your team's process. All code is open-source; your data stays on-premises.