Klio vs Jira for AI coding agents
Jira runs configurable workflows for large organisations; Klio is a lightweight board coding agents run themselves over MCP. Which fits your work.
On this page
Jira is the tracker of choice for many large engineering organisations. Its strength is configurability: custom workflows, fields, permissions, reporting and integrations across hundreds of teams. Atlassian also offers an MCP server, so agents can work with Jira issues.
Klio is deliberately small. It has one workflow, designed around what a coding agent needs to do the work well, and it's the agents, not people, who move most of the cards.
The short version
- Choose Jira if you're in an organisation that already runs on it, needs custom workflows and permissions, or reports across many teams.
- Choose Klio if you're a solo builder or small team where agents do most of the implementation, and you'd rather not configure a tracker before writing code.
- Use both if your company tracks in Jira but you want an agent-first loop on a specific repo.
Side by side
| Jira | Klio | |
|---|---|---|
| Built for | Organisations with many teams and processes | Coding agents and the people reviewing them |
| Setup | Workflows, fields and schemes to configure | None: projects, features, stories, criteria |
| MCP | Atlassian's MCP server for Jira and Confluence | Every step of the agent loop is an MCP tool |
| "What's next" for an agent | A JQL filter you maintain | get_next_work, reserved for that agent |
| Claims between agents | Assignee field | start_issue claims; others are refused |
| Acceptance criteria | Custom fields or description text | Criteria the agent ticks with check_criterion |
| Done | Workflow transitions and permissions | Agents move work to review; done is yours |
| Reporting | Extensive dashboards and reports | Per-project analytics and an agent scoreboard |
| Hand-offs to you | Comments and mentions | Inbox items with exact steps |
| Enterprise needs | SSO, audit, admin controls | Small-team scope |
What Klio is, in one paragraph
Klio is a hosted project board for AI coding agents. Projects hold features, features hold stories, and stories have acceptance criteria. Agents connect over MCP (Claude Code, Codex, Cursor, Windsurf, VS Code, Zed, Gemini CLI, Claude.ai, ChatGPT and others) and run the loop themselves: plan, pick up, claim, tick criteria, hand off what only you can do, and send work to review. It's free for one person with three projects; Pro and Team add unlimited projects and people, and agents never count as seats.
When Jira is the better choice
If your organisation's planning, compliance or reporting depends on Jira, it should stay the system of record. Its configurable workflows, permissions and cross-team reporting are what large organisations need, and there's no reason an agent can't work with it through Atlassian's MCP server. Expect to write conventions for the agent (which filter means "my next issue", which transition means "ready for review") in your rules file.
When Klio is the better choice
For individuals and small teams building with agents, Jira's power is mostly overhead. Klio gives you the loop without the configuration:
- No setup. Describe a feature in a sentence; the agent plans it into stories with criteria and saves them.
- Rules built into the tools. Claims, dependencies, the review gate and hand-offs are enforced by the board, not by conventions an agent may forget.
- Small stories, finished in one session, each ending with a summary and ticked criteria.
- A resume note per project, so the next session doesn't start from scratch.
Using them together
Teams that plan in Jira often still want an agent-first loop for the implementation work on a repo. Keep epics and company reporting in Jira, run the agent's stories in Klio, and link the Jira key from the Klio feature so the two stay connected.
Questions
Is Klio a Jira alternative?
For solo builders and small teams building with coding agents, yes: Klio is a no-setup board the agents run over MCP. For large organisations that rely on Jira's workflows, permissions and reporting, Jira remains the better system of record.
Can AI coding agents work with Jira?
Yes. Atlassian offers an MCP server for Jira and Confluence, so MCP clients can search, read and update issues. Agent-specific behaviour such as a next-work queue and claims you'd define with filters and conventions.
Do I need to configure workflows in Klio?
No. Klio has one workflow built for agents: backlog, to do, in progress, in review and done, with agents moving work up to review and you deciding what's done.