Model Context Protocol (MCP) server that connects Large Language Models with QA Sphere test-management data, enabling discovery, summarisation and chat over test cases.
https://github.com/Hypersequent/qasphere-mcpYour test cases are buried in a separate browser tab while you're deep in code. You need to check acceptance criteria, review edge cases, or understand test coverage - but switching contexts breaks your flow. The QA Sphere MCP server eliminates this friction by bringing your test management data directly into AI-powered IDEs.
Most developers lose momentum constantly switching between their IDE and test management tools. You're writing a feature, need to verify the acceptance criteria from QAS-1234, open a browser, navigate through QA Sphere, find the test case, then mentally context-switch back to your code.
This MCP server makes your QA Sphere test cases queryable and discoverable right from Claude Desktop, Cursor, or 5ire. No more browser tab juggling.
Code with full context: Ask your AI assistant "What are the acceptance criteria for the login flow tests?" and get instant answers from your actual test cases rather than outdated documentation.
Accelerated debugging: When a test fails in CI, query related test cases directly: "Show me all authentication tests that cover OAuth edge cases" without leaving your debugging session.
Smarter feature development: Before implementing a feature, ask "What existing test cases cover user registration validation?" to understand the current testing landscape and avoid gaps.
Test case analysis: Get AI-powered summaries of your test suites: "Summarize the test coverage for the payment module and identify potential gaps."
Feature Planning: You're tasked with adding two-factor authentication. Instead of manually searching QA Sphere, ask your AI assistant to pull all related security test cases and identify what needs updating.
Code Review Context: During PR reviews, reference specific test cases by ID to verify that implementation matches documented behavior: "Does this code change align with test case QAS-5671?"
Regression Analysis: When bugs surface, quickly identify which test cases should have caught the issue: "Find all test cases that cover user profile updates and their current status."
Documentation Generation: Generate developer-focused test summaries from your QA Sphere data to include in technical specifications or onboarding materials.
The server runs via npx - no local installation or complex configuration:
{
"mcpServers": {
"qasphere": {
"command": "npx",
"args": ["-y", "qasphere-mcp"],
"env": {
"QASPHERE_TENANT_URL": "your-company.region.qasphere.com",
"QASPHERE_API_KEY": "your-api-key"
}
}
}
}
Add this to your Claude Desktop, Cursor, or 5ire configuration, restart your IDE, and you're connected. The server handles API authentication and data formatting automatically.
This isn't another tool to learn - it extends your existing AI assistant with QA Sphere knowledge. Your natural language queries work exactly as expected:
The server translates these queries into QA Sphere API calls and returns formatted, actionable information.
Your test management data becomes as accessible as your codebase, eliminating the friction that slows down development cycles. When your AI assistant understands your testing context as well as your code context, you make better decisions faster.