If you’re responsible for keeping a CloverDX Server healthy, you most likely know the routine: checking Execution History, watching resource usage, and digging through logs when something doesn’t behave as expected.
And when an issue does show up, finding the real cause can sometimes be easy and sometimes take far longer than you have available.In this post — and video — I’ll show you how the new CloverDX Support Assistant lets you troubleshoot your Server faster by using AI to analyze logs, executions, performance, and configuration for you – potentially saving you hours of tedious work.
Even if you’re not deep into CloverDX day-to-day, the idea is simple: instead of hunting for answers manually, you can now ask AI questions about your Server – and get meaningful, actionable answers back.
What the Support Assistant does — and why it matters
The Support Assistant is powered by MCP (Model Context Protocol), which allows AI tools like ChatGPT or Claude to securely connect to your CloverDX Server and query diagnostic data directly.
That means you can:
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Ask questions in plain language
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Troubleshoot failing or unstable jobs
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Analyze Server performance and resource usage
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Detect memory and concurrency bottlenecks
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Identify risky jobs before they impact production
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Optimize scheduling and configuration
Reduce troubleshooting time from hours to minutes. In the video, I’m using the Claude desktop client connected to CloverDX via the MCP extension — but the same approach works with ChatGPT or any other LLM client you prefer (must be capable of MCP, of course).
The goal isn’t to replace your expertise. It’s to give you a faster path from symptom to root cause.
Getting started
You can start using the Support Assistant fairly easily — no major changes required. Even more so, you don’t necessarily have to upgrade to the latest CloverDX version.
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CloverDX Server 7.3+
MCP is built in and available out of the box.
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CloverDX Server 6.0–7.2
You can use a lightweight MCP Proxy (with a free license from the Customer Portal) to connect AI tools to your existing Server — no production upgrade required.
Once connected, you simply use a supported AI client (such as Claude Desktop or ChatGPT) and start asking questions about your Server.
Real examples
In the attached video, I walk through several practical troubleshooting scenarios you can easily repeat yourself. Here are the highlights — and why they matter.
Start with guided diagnostics
If you’re new to this, I recommend starting by launching the interactive diagnostic wizard, which provides pre-written prompts for common tasks like job analysis, health checks, and deployment reviews.
EXAMPLE 1
Finding the root cause of intermittent failures
Then, I’m showing how to analyze a job that fails only occasionally. The AI reviews ALL executions of the job (which would normally take ages, and one can miss something quite easily) and identifies a hidden pattern: In this case every failure occurred on February 29th due to a validation rule that didn’t handle leap day.
EXAMPLE 2
Checking overall job health
In the next scenario I ask the Support Assistant to review all scheduled jobs. It flags failing jobs, highlights common timing patterns, and explains what they have in common. This way you can get a high-level health view without manually reviewing each job.
EXAMPLE 3
Fixing scheduling conflicts
Then I’m using AI to identify multiple jobs starting at the same time and competing for memory – in this case it was a deliberate set up but in more complicated scenarios you can use AI to recommend a staggered schedule.
Built for operations — and for support
Another thing the Support Assistant can do for you if you reach a point where you need help from CloverDX Product Support, is that it can automatically collect and summarize relevant diagnostics for you and hand it over to the support team.
That means faster handover, better context, and quicker resolution.
Ask better questions. Get better answers.
The biggest shift the Support Assistant brings isn’t just faster troubleshooting — it’s a new way of thinking about Server operations.
Instead of asking where do I look?, you can ask what’s actually going on? — and let AI connect the dots across your CloverDX environment.
If there’s an issue you’ve never fully explained, this is the easiest way to finally get an answer.
Learn more and go deeper
If you want a deeper dive into troubleshooting best practices — including AI-assisted diagnostics — tune into the webinar “Healthy CloverDX Server: Troubleshooting”, where we explore real-world scenarios in more detail.
Watch the full tutorial of how AI can be used to maintain a healthy CloverDX Server:
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