Today, I want to share some customer feedback we’ve received. The first is an email I was sent from a startup customer excited to share how they’ve been able to automate many of their project management processes in Jira. How did they do it? They used AI, or to be more specific, they used Atlassian’s remote MCP server and Claude. So, with their permission, prepare to be amazed!

The email:
We spent a few hours yesterday setting up our first project in Jira using 100% Claude - and the results were AMAZING.
This is game-changing for project management, where AI-first teams were struggling to PM with good collaboration tools.
We used Claude to create epics, stories, subtasks, add story points, and more. As we complete each issue, Claude commits and logs directly into Jira. We are now implementing a smart-allocation feature that will automatically delegate issues to the right team member.
But wait, there’s more!
The customer above isn’t the only one buzzing about Atlassian’s MCP server! One of our CSM leaders received this feedback from a friend/neighbor:
"Your products are so good. We run so much of our business through Jira and Confluence, but your MCP has completely changed our workflows."
🤖 Here were some of the highlights they shared:
- Prompting Claude to summarize team priorities in Jira (key actions, tickets, etc)
- Asking for what might be missing that has an impact on the product roadmap
- Querying Intercom's mcp to prioritize feature development based on real-time customer issues
- Querying Confluence to summarize things, build new pages (or update) based on outside inputs
Cool, right? So, if you’re not sure what everyone is talking about, please read on…
MC-what-now and who is Claude?
If you’re like I was until recently, and you’re now thinking - MC-what-now and who exactly is Claude? Let me explain! First, a quick overview of Atlassian’s AI features - Atlassian products offer AI through our Atlassian Intelligence and Rovo features. And, in a nutshell, this is what each does:
Atlassian Intelligence |
Rovo |
| Scope: Individual Atlassian cloud products, such as Jira, Confluence, Bitbucket, etc. |
Scope: Rovo searches across multiple Atlassian cloud products and other third-party tools via connectors.
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Features:
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Search for content within Jira, Confluence, etc.
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Generate and transform content
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Create automation rules
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Summarize Jira issues and Confluence pages, comments, and blogs
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Define terms in Confluence
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Summarize and preview Smart Links from Confluence, Jira, and Google docs
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Features:
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Rovo Search - access your company's data across Atlassian and connected 3rd party apps
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Rovo Chat - conversational interface for tasks like finding answers, generating ideas, etc.
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Rovo Agents - configurable AI teammates to collaborate and move work forward
- Studio App - create everything from AI agents to automation and apps in one unified experience
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So, hopefully that clarifies Atlassian Intelligence vs Rovo, so, what’s this MCP server thing?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to AI large language models or LLMs. Think of MCP like a USB-C for AI applications. Just as USB-C provides a standardized port to connect and charge your stuff, MCP provides a standardized way to connect AI models to different data sources and tools.
So, Atlassian’s MCP server gives you a way to connect Atlassian’s data and AI to other AI tools, such as Anthropic’s Claude. And, what do we get if we connect these different AI tools?

NO, NOT Skynet and terminators!
We get the ability to access information from Jira and Confluence wherever you use your other AI tools (right now, that’s Claude). This lets you do all sorts of things like:
- Summarize Jira work items or Confluence pages
- Create Jira work items or Confluence pages directly from Claude
- Get the model to take multiple actions in one go, like creating issues or pages in bulk
- Enrich Jira work items with context from many different sources that Claude has access to
- And so much more!
Wanna learn more?
Here’s some great resources on Rovo and Atlassian’s MCP server so you can learn more.
Atlassian Intelligence:
Rovo:
MCP server:
In the comments let us know how you plan to use AI, Rovo or MCP!