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Manage Jira Cloud projects, issues, sprints, and worklogs from AI clients.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Jira MCP Server" yet — see the docs or source repo.
Read the issues in my current Jira Cloud sprint, group them by assignee, summarize blockers, change all high-priority issues in 'To Do' to 'In Progress', and then provide a changelog.
A grouped issue overview by assignee, a blocker summary, and a changelog of updated issue statuses.
Create a high-severity bug in the Jira mobile project: app crashes after login. Include reproduction steps and expected result; after creation, automatically add a comment and @mention the QA team for verification.
A new bug issue with a structured description and an added comment notifying the QA team.
Analyze this sprint's board, completed issues, and worklogs, then produce a weekly report including completion rate, delayed issues, logged hours per team member, and key risks to watch next week.
A structured sprint weekly report with progress metrics, delayed items, team worklog totals, and risk alerts.
Connect Jira Cloud to manage projects, boards, issues, and time tracking.
Let AI work with Jira Cloud to query issues, comment, and find users.
Connect to Jira conversationally to query issues, log work, comment, and run JQL.
Give AI read-only Jira Cloud access for projects, sprints, issues, and JQL.
Manage Jira Cloud projects, issues, sprints, and releases using natural language.
Manage Jira Cloud issues, comments, transitions, and attachments using natural language.