MicroShift Test Analyzer

MicroShift Test Analyzer is an MCP server that connects to Google Sheets to extract, parse, and analyze automated test failures across various MicroShift releases. Built using FastMCP and the Model Context Protocol Python SDK, it allows quality assurance engineers, DevOps professionals, and platform developers to inspect CI/CD execution trends directly from an AI client like Claude Desktop. The server ingests structured spreadsheet logs capturing test architectures, frameworks like RobotFramework and Ginkgo, execution statuses, and failure logs. Users can query the server to aggregate failure frequencies, track pipeline reliability trends over time, compare test stability across distinct release versions, and locate recurring errors using text search. By bridging live spreadsheet data with conversational AI interfaces, MicroShift Test Analyzer simplifies root cause discovery, automates release readiness evaluations, and eliminates manual triage across complex multi-architecture deployment matrices.

Category: Data & Analytics

Tags: ci/cd, failure analysis, google sheets, microshift, test automation

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How to install and configure MicroShift Test Analyzer

1. Clone the repository and install requirements: bash pip install -r requirements.txt 2. Set up a Google Cloud service account with the Google Sheets API enabled, share your target sheet with the service account email, and configure .env: bash cp env.example .env GOOGLE_CLIENT_EMAIL=your-service-account@your-project.iam.gserviceaccount.com GOOGLE_PRIVATE_KEY="-----BEGIN PRIVATE KEY-----\nYour private key content\n-----END PRIVATE KEY-----\n" 3. Adjust the SPREADSHEET_ID in server.py to point to your spreadsheet. 4. Register the server in your Claude Desktop configuration file (claude_desktop_config.json): json { "mcpServers": { "microshift-test-analyzer": { "command": "python", "args": ["/absolute/path/to/mcp-test-scenarios-server/server.py"], "cwd": "/absolute/path/to/mcp-test-scenarios-server" } } } 5. Restart Claude Desktop to begin querying test results.

What you can do with MicroShift Test Analyzer

• Grouping failed CI pipelines by specific MicroShift target releases to identify regressions across version boundaries. - Generating aggregate failure summaries grouped by pipeline, release version, or specific error reason strings. - Analyzing testing pipeline stability trends across configurable historical windows to detect flaky test scenarios. - Searching for specific failure root causes across all recorded architecture and framework test logs. - Comparing overall test execution results between two target MicroShift versions to confirm fix deployments.

Key facts

• https://github.com/kasturinarra/mcp-test-scenarios-server
• Data & Analytics, DevOps, CI/CD & Version Control
• ci/cd, failure analysis, google sheets, microshift, test automation

Part of MCP Servers

How do I install MicroShift Test Analyzer?

Install project dependencies using pip install with the requirements.txt file. Create a Google Cloud service account, enable the Google Sheets API, download your JSON key, and add your credentials to a local .env file. Next, update your spreadsheet ID in server.py and configure the server entry within your Claude Desktop configuration file.

What can MicroShift Test Analyzer do?

MicroShift Test Analyzer provides tools to inspect test outcomes stored in Google Sheets. It can retrieve failed pipelines grouped by version, generate failure summaries, analyze historical pipeline trends over custom timeframes, run keyword searches across failure messages, and perform version-to-version result comparisons.

Which MCP clients work with MicroShift Test Analyzer?

MicroShift Test Analyzer communicates over standard input and output using the Model Context Protocol Python SDK. It works with Claude for Desktop and any other MCP-compliant client that supports executing local Python server processes.

What Google Sheet structure does the server expect?

The server expects a sheet with columns for date, execution ID, MicroShift target, brew build version, and release version in columns A through E. Column F and onward must contain pipeline records with architecture, test type, framework, status, and failure reason details separated by line breaks.