AI Enhanced usage of Zephyr Scale (server / datacenter)

We're currently evaluating how to extend our use of Zephyr Scale (on jira datacenter) by integrating AI-driven capabilities. We're curious if others in the community have explored similar ideas or already implemented something along these lines.

Here are a few areas we're looking into:

• Test Case Generation via AI: Are there any Jira plugins or external tools (using the zephyr scale api) that can auto-generate test cases based on requirements, user stories, or code? We're especially interested in solutions that can push directly into Zephyr Scale or sync via Jira issues.
• API Integration via MCP: Has anyone used MCP (or similar integration platforms) to work with Zephyr Scale's REST API for managing test cases, results, or execution plans? We'd like to know what's feasible in terms of connecting AI services through that layer.
• Other AI Use Cases: Are there tools you're using to enhance your test planning, prioritization, or traceability workflows with AI? This could include:
• GPT-based summarization of test results or bug reports
• Suggesting missing test coverage based on code diffs
• Auto-linking defects to test executions

If you’ve found something that works (or doesn’t), drop a comment or message. Happy to compare notes or collaborate.