TestRail MCP Server

TestRail MCP Server

A Model Context Protocol server that provides integration with TestRail, allowing AI assistants to interact with TestRail projects, test cases, test runs, and results.

Category
访问服务器

README

TestRail MCP Server

A Model Context Protocol (MCP) server that provides integration with TestRail, allowing AI assistants to interact with TestRail projects, test cases, test runs, and results.

Features

Tools

  • get_projects: Retrieve all TestRail projects
  • get_project: Get details of a specific project
  • get_test_cases: Retrieve test cases with optional filtering
  • create_test_case: Create new test cases
  • get_test_runs: Retrieve test runs for a project
  • create_test_run: Create new test runs
  • add_test_result: Add test results to test runs
  • get_users: Retrieve TestRail users
  • test_connection: Test the connection to TestRail
  • parse_testrail_url: 🆕 Parse TestRail URLs and auto-call appropriate tools

Resources

  • testrail://projects: Access to all TestRail projects
  • testrail://users: Access to all TestRail users

Prompts

  • test_case_template: Generate comprehensive test case templates
  • test_run_summary: Generate detailed test run summary reports

Installation

  1. Clone this repository:
git clone <repository-url>
cd mcp-testrail
  1. Install dependencies:
npm install
  1. Build the project:
npm run build

Configuration

Create a .env file in the root directory with your TestRail configuration:

TESTRAIL_URL=https://your-company.testrail.io
TESTRAIL_USERNAME=your-email@company.com
TESTRAIL_API_KEY=your-api-key
DEFAULT_PROJECT_ID=1

Getting TestRail API Credentials

  1. Log in to your TestRail instance
  2. Go to your user profile (click on your name in the top-right corner)
  3. Navigate to the "API Keys" tab
  4. Generate a new API key
  5. Use your email address as the username and the generated key as the API key

Usage

With Claude Desktop

Add the server to your Claude Desktop configuration file (claude_desktop_config.json):

{
  "mcpServers": {
    "testrail": {
      "command": "node",
      "args": ["/path/to/mcp-testrail/dist/index.js"],
      "env": {
        "TESTRAIL_URL": "https://your-company.testrail.io",
        "TESTRAIL_USERNAME": "your-email@company.com",
        "TESTRAIL_API_KEY": "your-api-key"
      }
    }
  }
}

Direct Usage

You can also run the server directly:

npm start

Or in development mode:

npm run dev

Development

Project Structure

src/
├── index.ts              # Main MCP server implementation
├── testrail-client.ts    # TestRail API client
└── types.ts              # TypeScript type definitions

Available Scripts

  • npm run build: Build the TypeScript project
  • npm run watch: Build and watch for changes
  • npm start: Start the compiled server
  • npm run dev: Start the server in development mode with ts-node
  • npm run lint: Lint the source code

Building

npm run build

Testing

Test the connection to TestRail:

npm run dev
# Then use the test_connection tool

API Coverage

This MCP server covers the following TestRail API endpoints:

Projects

  • GET /get_projects - Get all projects
  • GET /get_project/{id} - Get project details

Test Cases

  • GET /get_cases/{project_id} - Get test cases
  • GET /get_case/{id} - Get test case details
  • POST /add_case/{section_id} - Create test case
  • POST /update_case/{id} - Update test case

Test Runs

  • GET /get_runs/{project_id} - Get test runs
  • GET /get_run/{id} - Get test run details
  • POST /add_run/{project_id} - Create test run
  • POST /close_run/{id} - Close test run

Test Results

  • GET /get_results/{test_id} - Get test results
  • POST /add_result/{test_id} - Add test result
  • POST /add_result_for_case/{run_id}/{case_id} - Add result for specific case

Users

  • GET /get_users - Get all users
  • GET /get_user/{id} - Get user details

Suites & Sections

  • GET /get_suites/{project_id} - Get test suites
  • GET /get_sections/{project_id} - Get sections
  • GET /get_milestones/{project_id} - Get milestones

Examples

URL Parsing (New Feature!)

Simply paste any TestRail URL and get the data automatically:

// Parse a test case URL
{
  "url": "https://moneyforward.tmxtestrail.com/index.php?/cases/view/2322865"
}
// Automatically detects it's a test case and retrieves case ID 2322865

// Parse a test run URL  
{
  "url": "https://company.testrail.io/runs/view/456"
}
// Automatically detects it's a test run and retrieves run details

// Parse test cases list with filters
{
  "url": "https://company.testrail.io/cases/123?suite_id=5&section_id=10"
}
// Automatically retrieves filtered test cases

Creating a Test Case

// Using the create_test_case tool
{
  "sectionId": 123,
  "title": "Test user login functionality",
  "type_id": 1,
  "priority_id": 2,
  "custom_steps_separated": [
    {
      "content": "Navigate to login page",
      "expected": "Login page is displayed"
    },
    {
      "content": "Enter valid credentials",
      "expected": "User is logged in successfully"
    }
  ]
}

Adding Test Results

// Using the add_test_result tool
{
  "runId": 456,
  "caseId": 789,
  "status_id": 1, // Passed
  "comment": "Test executed successfully",
  "elapsed": "5m",
  "version": "v1.2.3"
}

Error Handling

The server includes comprehensive error handling and will return detailed error messages for:

  • Invalid TestRail credentials
  • Network connectivity issues
  • Invalid parameters
  • TestRail API errors

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

License

MIT License - see LICENSE file for details.

Support

For issues and questions:

  1. Check the TestRail API documentation
  2. Verify your credentials and network connectivity
  3. Check the server logs for detailed error messages
  4. Open an issue in this repository

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选