BluBees

Beta is where we ship and learn. v4.2.0 is our October update; Bitbucket is now a fully supported connector, closing the version control gap for teams not on GitLab. Node configuration auto-inherits in chained workflows, removing a persistent friction point. And backend security has been hardened across all services. Three things, done properly.

Beta is where we ship and learn. v4.1.0 is our latest update — focused on visibility and workflow control. Step Execution Status brings live status to every node on the canvas. Flow Variables let you store and reuse values without rebuilding logic. Array Splitter handles list data item by item, in sequence or in parallel. Here's everything that shipped.

When we launched BluBees on the Atlassian Marketplace, we knew the real work was just beginning. Building something genuinely useful means getting it in front of real teams, watching how they use it, and iterating on what actually matters. That's what Beta is for. And today, we're sharing everything that's in it — MCP support, four AI models, Webhook Node, Conditional Routes, and a canvas built for everyone on your team.

Most software teams have automated parts of their release pipeline. The CI/CD runs automatically. Tests fire on merge. But the full pipeline — from the moment a customer reports something to the moment a fix is deployed and everyone who needs to know has been told — still has humans filling the gaps. Someone creates the Jira ticket. Someone updates the status. Someone notifies Slack. These aren't engineering tasks. They're coordination tasks. And they happen every single rele

We spent the last decade automating tasks. If-this-then-that. It saved time, and for a while it felt like the future. But even the most automated organisations still have humans filling gaps, not because the automation broke, but because automation only handles what you anticipated. The moment something requires judgment, it stops. That ceiling has a name. And what's being built beyond it does too. This is about the shift from automation to intelligent orchestration, and why

You've done the hard part, the tests run automatically, the results come in automatically. And then a human has to read them, manually create Jira bugs for every failure, notify Slack, update the release tracker, and write the Confluence summary. The tests are automated. Everything that happens because of the tests is still manual. That's the QA automation gap, and most teams don't notice it until someone asks why QA is still the bottleneck in a team that runs automated tests

MCP, Model Context Protocol, is showing up everywhere in the Atlassian ecosystem right now. But most of the conversation assumes you already know what it is. This post starts from the beginning: what MCP is, why it exists, and why it matters specifically for teams using Jira. The short version: it's the standard that lets AI models talk to your tools, and act on them, without custom integration work for every combination. And it changes a lot about what's possible.

BluBees just launched on the Atlassian Marketplace. Rather than write a post about what we built, we wanted to start with why we built it. Here's something most Jira users recognise but rarely say out loud: Jira doesn't actually run your work. It records it. The real problem is everything that happens in the space between your tools — the manual updates, the missed handoffs, the copy-pasting between Slack and Jira and email. Nobody has solved that from inside Jira. Until now.