I posted a few months ago about some of the Rovo agents I created, and what I thought of the experience.
Like everyone else on LinkedIn, I’ve been deep in Claude exploration, and this time I want to share how I’ve combined Claude and Rovo or the Atlassian MCP for two processes.
I get pinged on a lot of Confluence pages and Jira issues. “@Laura what do you think?” “@Laura is this okay?” “@Laura just updated”. Three days later, I remember someone is waiting for my feedback, just not where and for which topic! I don’t love the notification feed as it tends to get cluttered with non-essential updates (“Your Loom was watched!”), and I’m drowning in notification emails.
A long time ago I tried setting up a filter in Jira to catch all the times someone mentioned me in a comment, but this only works if my name is in text, not a user mention, because @mentions are stored as structured "mention" nodes in Atlassian Document Format, not in searchable text. There's no JQL field like comment-mentions = currentUser() or mentioned-in-comment = accountId.
How Claude did the heavy lifting querying IDs & applying regex
Claude uses the MCP Atlassian connector to run a JQL query searching for open issues where I’m mentioned, and then checks the comments of each issue. It can extract plain text recursively from content nodes, treating type: "text" nodes as text and type: "mention" nodes as @displayName.
Then it runs a CQL query with mention = "accountId" (since Confluence supports this), and checks if the comment is resolved or not.
Claude then applies its own regex-based filtering to figure out which mentions are actually asking me to do something vs. just name-dropping me.
Then it age-buckets the results, displays it in a nice html format with links to the page or Jira work item 😀 I didn’t know where to start to build something on my own that could analyze Atlassian Document Format or apply regex-based filtering; thankfully Claude built it for me!
Preparing a content brief for someone to write a blog or article requires completing keyword research, Jira/Confluence best practice research, and then also research about the product I want to include in the article.
Claude can help with the first 2 types of research, notably with the MCP server from our keyword tool, but it tends to have a hard time finding the right information about my company's products on it’s own. Searching the internet leads to too many hallucinations or just incorrect conclusions.
But I already built a Rovo agent to answer questions about our products! This Rovo agent has custom knowledge with curated pages, so I know the results it gives will be much more accurate than if I just searched our entire Confluence site.
So I just included a query to our Rovo agent as part of the Claude skill to get the right information. Right now there’s no API to query Rovo agents, so I have to use Claude in Chrome, but it works pretty well. Claude opens a new tab, enters it’s question, and takes the answer from Rovo for the next part of the process.
Once Claude has fetched the information from Rovo, it combines all the research into a nice format, and asks me where I want to create a Confluence page.
Currently I find it is seamless to create new pages under parent pages, but Claude sometimes struggles to create pages under folders and has to do several attempts.
Things have changed dramatically since I wrote my other article about creating Rovo agents. I’m sure in 6 months time the way Claude and Rovo or the Atlassian MCP can be used together will allow for vastly more sophisticated processes.
Laura Campbell
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