MCP Test Failure Analysis Server

MCP Test Failure Analysis Server

Provides tools to analyze test failures, cluster similar failures, and detect flaky tests from input or log files, helping QA teams debug and triage issues.

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README

MCP Server Demo

This project contains Python MCP servers for QA-oriented test failure analysis, built with FastMCP.

<img width="1920" height="1080" alt="image" src="https://github.com/user-attachments/assets/dcb39a24-21c8-4658-8ca3-ed3fe549735e" />

Current Structure

mcp-server-demo/
├── FailureAnalysisFromLogs.py
├── README.md
├── logs/
├── pyproject.toml
├── testFailureAnalysis.py
└── uv.lock

What This Project Includes

  • testFailureAnalysis.py
    • analyze_test_failure
    • cluster_failures
    • detect_flaky_tests
  • FailureAnalysisFromLogs.py
    • analyze_test_failure
    • Reads and classifies local .log files from the logs/ folder
  • logs/
    • Sample failure logs used by the log-based MCP server
  • pyproject.toml
    • Python version and dependency configuration
  • uv.lock
    • Locked dependency versions for reproducible installs
  • .vscode/mcp.json
    • MCP server entries for test-failure-analysis, test-failure-analysis-from-logs, and mcp-atlassian

Prerequisites

  • Python 3.11 or later
  • uv
  • Internet access for the first dependency install

Installation

From the repository root:

cd mcp-server-demo
uv sync

Running the Server

Start the input-based MCP server with:

uv run python testFailureAnalysis.py

Start the log-based MCP server with:

uv run python FailureAnalysisFromLogs.py

Available Tools

analyze_test_failure

Analyzes a failed test using the test name, stack trace, and logs, then returns a likely failure category and recommendation.

analyze_test_failure in FailureAnalysisFromLogs.py

Analyzes local .log files from the logs/ folder and returns failure classification, likely root cause, recommendation, and important error lines. It can analyze all logs, a specific test name, or an exact log file name.

cluster_failures

Groups similar failures by stack trace signature so repeated patterns are easier to spot.

detect_flaky_tests

Reviews historical pass/fail results and identifies tests that show flaky behavior.

Optional Local MCP Configuration

The repository root contains .vscode/mcp.json, which can be used by MCP-aware tooling for local server setup during development. It includes entries for test-failure-analysis, test-failure-analysis-from-logs, and mcp-atlassian.

Atlassian MCP

The local MCP configuration includes an mcp-atlassian server entry for Jira access.

How to use it

Use the configured mcp-atlassian entry from .vscode/mcp.json in your MCP-aware client.

To run it manually, use:

JIRA_URL=<your-jira-url> \
JIRA_USERNAME=<your-jira-username> \
JIRA_API_TOKEN=<your-jira-api-token> \
uvx mcp-atlassian

Troubleshooting

  • If uv is not available, install it and reopen the terminal.
  • If dependency installation fails, confirm Python 3.11+ is active.
  • If the server does not start, run uv sync again inside mcp-server-demo.

Work Flow Image in Image folder at image/project-workflow.png

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