Check Jira and Confluence without leaving the conversation

Overview

The Atlassian Rovo MCP connector lets Spark search, read, and act on Jira, Confluence, Jira Service Management, Bitbucket, and Compass through conversation. Ask what a project's issues say, what a space documents, or what a component depends on, and the answer comes from live Atlassian data. Each user connects their own Atlassian account, and Rovo scopes every request to that account's existing permissions.

Search and update Jira issues without leaving Spark

Ask Spark to find issues by JQL, check an issue's status and links, or pull field and project metadata while you're scoping a feature. When the update is the natural next step, ask Spark to create an issue, edit one, add a comment or worklog, or move it to its next status.

Pull Confluence pages into the conversation

Ask Spark to search Confluence by CQL or browse a space's pages and their descendants, including footer and inline comments, to check what's already documented before you draft. Spark can also create or update a page, or add a comment, when you want to capture a decision back in Confluence.

Reach Jira Service Management, Bitbucket, and Compass through the same connection

The same connector reaches Ops alerts, schedules, and team information in Jira Service Management, repositories, pull requests, and pipelines in Bitbucket, and component and ownership data in Compass. Ask Spark about any of these when a feature discussion touches an incident, a repo, or a service catalog entry.

Setup

Any Spark user can connect Atlassian Rovo. No admin setup is required in Productboard, though an Atlassian org admin may restrict which AI clients can connect, require API-token authentication, or turn off specific tool groups on their side.

From any Spark chat, open the connectors modal, click Connect next to Atlassian Rovo, then complete the sign-in on Atlassian's page and authorize access. You'll return to Productboard with the connection active in every Spark chat.