Allure Test Reports

by crisschan

1 stars
381 downloads
Not rated
GitHub

About

Provides a bridge to Allure test reports, enabling access to test execution data including test cases, steps, statuses, and timestamps through a structured API for analysis and custom reporting.

Details

Author
crisschan
Repository
crisschan/mcp-allure
GitHub stars
1
Downloads
381
License
Apache License 2.0
Categories
Developer Tools, Other, Productivity, Design, Workplace, AI, Knowledge Base, Communication, Frontend

- Conversion: Converts Allure test reports into LLM-friendly formats.
- Optimization: Optimizes test reports for AI consumption.
- Efficiency: Converts test reports efficiently.
- Cost: Converts test reports at a low cost.
- Accuracy: Converts test reports with high accuracy.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Allure Test Reports
    Command (node, npx, python, etc.) uv
    Arguments
    • Argument 1 run
    • Argument 2 --with
    • Argument 3 mcp[cli]
    • Argument 4 mcp
    • Argument 5 run
    • Argument 6 /Users/crisschan/workspace/pyspace/mcp-allure/mcp-allure-server.py

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

To install mcp-repo2llm using uv:

{
"mcpServers": {
"mcp-allure-server": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"/Users/crisschan/workspace/pyspace/mcp-allure/mcp-allure-server.py"
]
}
}
}

get_allure_report

Reads Allure report and returns JSON data. Input: report_dir (string) - Allure HTML report path. Returns: String, formatted JSON data.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "allure test reports": {
            "cwd": null,
            "env": {},
            "args": [
                "run",
                "--with",
                "mcp[cli]",
                "mcp",
                "run",
                "/Users/crisschan/workspace/pyspace/mcp-allure/mcp-allure-server.py"
            ],
            "shell": false,
            "command": "uv"
        }
    }
}

Linux

{
    "cwd": null,
    "env": [],
    "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "/Users/crisschan/workspace/pyspace/mcp-allure/mcp-allure-server.py"
    ],
    "shell": false,
    "command": "uv"
}

Macos

{
    "cwd": null,
    "env": [],
    "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "/Users/crisschan/workspace/pyspace/mcp-allure/mcp-allure-server.py"
    ],
    "shell": false,
    "command": "uv"
}

Windows

{
    "cwd": null,
    "env": [],
    "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "/Users/crisschan/workspace/pyspace/mcp-allure/mcp-allure-server.py"
    ],
    "shell": false,
    "command": "uv"
}

MCP-Allure is a MCP server that reads Allure reports and returns them in LLM-friendly formats.

As AI and Large Language Models (LLMs) become increasingly integral to software development, there is a growing need to bridge the gap between traditional test reporting and AI-assisted analysis. Traditional Allure test report formats, while human-readable, aren't optimized for LLM consumption and processing.

MCP-Allure addresses this challenge by transforming Allure test reports into LLM-friendly formats. This transformation enables AI models to better understand, analyze, and provide insights about test results, making it easier to:

- Generate meaningful test summaries and insights
- Identify patterns in test failures
- Suggest potential fixes for failing tests
- Enable more effective AI-assisted debugging
- Facilitate automated test documentation generation

By optimizing test reports for LLM consumption, MCP-Allure helps development teams leverage the full potential of AI tools in their testing workflow, leading to more efficient and intelligent test analysis and maintenance.

- Efficiency: Traditional test reporting formats are not optimized for AI consumption, leading to inefficiencies in test analysis and maintenance.
- Accuracy: AI models may struggle with interpreting and analyzing test reports that are not in a format optimized for AI consumption.
- Cost: Converting test reports to LLM-friendly formats can be time-consuming and expensive.

- Conversion: Converts Allure test reports into LLM-friendly formats.
- Optimization: Optimizes test reports for AI consumption.
- Efficiency: Converts test reports efficiently.
- Cost: Converts test reports at a low cost.
- Accuracy: Converts test reports with high accuracy.

{ "mcpServers": { "mcp-allure-server": { "command": "uv", "args": [ "run", "--with", "mcp[cli]", "mcp", "run", "/Users/crisschan/workspace/pyspace/mcp-allure/mcp-allure-server.py" ] } } }

- Reads Allure report and returns JSON data
- Input:

- report_dir: Allure HTML report path

{ "test-suites": [ { "name": "test suite name", "title": "suite title", "description": "suite description", "status": "passed", "start": "timestamp", "stop": "timestamp", "test-cases": [ { "name": "test case name", "title": "case title", "description": "case description", "severity": "normal", "status": "passed", "start": "timestamp", "stop": "timestamp", "labels": [ ], "parameters": [ ], "steps": [ { "name": "step name", "title": "step title", "status": "passed", "start": "timestamp", "stop": "timestamp", "attachments": [ ], "steps": [ ] } ] } ] } ] }

This is a web browser that enables your coding agent, such as Claude Code, to visit websites on your behalf and assist you in identifying bugs or creating UI test cases.

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