A
licenseA
qualityB
maintenanceQA Sphere MCP server that enables Large Language Models to interact directly with test management system test cases, supporting AI-powered development workflows and test case discovery.
15
101
23
MIT
MCP-Allure
by crisschan
MCP-Allure
MCP-Allure 是一个 MCP 服务器，可以读取 Allure 报告并以 LLM 友好的格式返回它们。
动机
随着人工智能和大型语言模型 (LLM) 在软件开发中日益重要，弥合传统测试报告与人工智能辅助分析之间差距的需求也日益增长。传统的 Allure 测试报告格式虽然易于阅读，但并未针对 LLM 的使用和处理进行优化。
MCP-Allure 通过将 Allure 测试报告转换为 LLM 友好格式来解决这一挑战。这种转换使 AI 模型能够更好地理解、分析并提供关于测试结果的洞察，从而更轻松地：
生成有意义的测试摘要和见解
识别测试失败的模式
针对失败的测试提出潜在的修复建议
实现更有效的 AI 辅助调试
促进自动化测试文档生成
通过优化 LLM 使用的测试报告，MCP-Allure 帮助开发团队在测试工作流程中充分利用 AI 工具的潜力，从而实现更高效、更智能的测试分析和维护。
已解决的问题
效率：传统的测试报告格式并未针对人工智能的使用进行优化，导致测试分析和维护效率低下。
准确性：人工智能模型可能难以解释和分析未针对人工智能消费进行优化格式的测试报告。
成本：将测试报告转换为 LLM 友好格式可能既耗时又昂贵。
主要特点
转换：将 Allure 测试报告转换为 LLM 友好格式。
优化：优化 AI 消耗的测试报告。
效率：高效转换测试报告。
成本：以低成本转换测试报告。
准确性：以高精度转换测试报告。
安装
要使用 uv 安装 mcp-repo2llm：
{
"mcpServers": {
"mcp-allure-server": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"/Users/crisschan/workspace/pyspace/mcp-allure/mcp-allure-server.py"
]
}
}
}工具
获取魅力报告
读取Allure报告并返回JSON数据
输入：
report_dir：Allure HTML报告路径
返回：
字符串，格式化的JSON数据，像这样：
{
"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": [
]
}
]
}
]
}
]
}
Maintenance
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Commit activity
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