Search Jira issues using JQL queries to find specific tickets by project, status, assignee, or custom criteria. Returns issue keys and titles for quick identification.
Analyze failed tests in Zebrunner launches to identify root causes, group similar errors, and generate Jira tickets with recommendations for efficient debugging.
Search across Jira tickets, meeting transcripts, and documentation to answer freeform questions about codebase, architecture, or past decisions. Natural language queries.
Enables AI models to interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.
Create Jira tickets such as Story, Task, Bug, or Sub-task by providing project key, summary, and issue type. Optionally add description, labels, due dates, and time estimates.
Retrieve Jira issues by submitting a JQL query to filter and fetch specific results, with options to limit the number of returned entries using the Jira MCP Server.
Bulk create Jira issues using field dictionaries for multiple entries. Specify issue types like 'Bug', 'Task', or 'Story' as per your Jira instance, and optionally reload created issues.