{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/0c124aeaa86643a9babf600c6bc45c38\" frameborder=\"0\" width=\"2056\" height=\"1542\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1542,"width":2056,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1542,"thumbnail_width":2056,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/0c124aeaa86643a9babf600c6bc45c38-3be9d67417719384.gif","duration":374.275,"title":"Enhancing AI Context: Teamwork Graph MCP Tools in Atlassian Rovo Server","description":"In this demo, I introduced two new tools we've added to the Atlassian Rovo MCP server: GetTeamworkGraphContext and GetTeamworkGraphObject. These tools are designed to enhance our AI agent's ability to provide context around work items, particularly in scenarios where the answers have been vague. By using GetTeamworkGraphContext, we can identify all connected objects to a specific Jira work item, while GetTeamworkGraphObject allows us to retrieve detailed data for those objects. The goal is to first discover related items and then return the essential details. I encourage you to explore these tools to improve your interactions with our AI."}