Search, read, and update Jira, Confluence, Bitbucket, and Compass from a Spark chat.
The Atlassian Rovo MCP connector lets Spark search, read, and act on Atlassian products through conversation.
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.
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.
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.
Any Spark user can connect Atlassian Rovo with their own Atlassian account, and Rovo scopes every request to that account's existing permissions. 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.
Search and read Google Drive files from Productboard Spark with a read-only MCP connector.
Search, review, and update Trello boards and cards from Productboard Spark through Trello's MCP server.
Check, build, and iterate on Lovable prototypes through natural language in Productboard Spark.