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MCP Zebrunner
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MCP Zebrunner

The Zebrunner MCP Server is an AI assistant tool integrated with Zebrunner test case management, helping QA teams manage test cases, test suites, and execution data through natural language, including an intelligent rule system and code generation functions.
Developer toolsArtificial intelligence chatbots#Test management#AI assistant#Quality verification#Code generation.TypeScript
2 points
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Overview

Installation

Content Details

Alternatives

What is Zebrunner MCP Server?

This is an intelligent connection tool that allows you to interact directly with the Zebrunner test management platform through an AI assistant (such as Claude). You only need to ask questions in natural language to obtain test information, analyze test coverage, generate test code, and get intelligent improvement suggestions.

How to use Zebrunner MCP Server?

After installation and configuration, you can directly ask test - related questions in AI assistants such as Claude, for example: 1. "Get the list of test suites for project MCP" 2. "Analyze the quality of test case MCP - 123" 3. "Generate automation code for test case MCP - 456" The AI assistant will automatically call the corresponding tools and return the results.

Applicable scenarios

Suitable for all roles that need to interact with the test management platform: • QA engineers: Quickly find and verify test cases • Automation engineers: Generate and verify test code • Developers: Understand test requirements and verify implementations • Test managers: Obtain test coverage and quality reports • Product managers: Understand the project test status and risks

Main features

Intelligent rule system
A three - layer intelligent rule system automatically verifies the quality of test cases, including core quality standards, detailed checkpoints, and technical configuration rules.
Test case management
Retrieve, filter, and analyze test cases through natural language, supporting searches by multiple conditions such as title, status, and priority.
Test suite organization
View and manage the hierarchical structure of test suites to understand the organization and coverage of tests.
Test coverage analysis
Analyze the coverage between test cases and implementation code to identify missing test steps.
Test code generation
Automatically generate test code frameworks in languages such as Java, Python, and JavaScript based on test cases.
Launch and execution management
Obtain detailed information about test execution, including launch status, test results, and failure analysis.
Reporting and analysis
Generate test quality reports, failure analysis, and platform performance statistics, supporting multiple output formats.
URL intelligent analysis
Directly paste the Zebrunner URL, and the AI will automatically identify and analyze the corresponding test or launch information.
Duplicate test analysis
Intelligently identify duplicate or similar test cases in test suites to improve test efficiency.
Screenshot analysis
Download and analyze screenshots of test failures, and identify problems by combining OCR and AI visual analysis.
Advantages
Natural language interaction: No need to learn complex commands, just ask questions in daily language.
Intelligent analysis: AI automatically analyzes test quality and provides improvement suggestions.
Suitable for multiple roles: Provide customized functions for different roles such as QA, development, and managers.
Save time: Automate repetitive tasks such as test case verification and code generation.
Easy integration: Seamlessly integrate with AI assistants such as Claude Desktop/Code.
Customizable rules: Customize verification rules and quality standards according to project requirements.
Limitations
Requires a Zebrunner account: Must have valid access rights to a Zebrunner instance.
Initial configuration: Requires correct configuration of environment variables and API credentials.
Network dependency: Requires a stable network connection to access the Zebrunner API.
Learning curve: Although the interaction is simple, basic test management concepts need to be understood.
Function limitations: Limited by the functionality provided by the Zebrunner API.

How to use

Environment preparation
Ensure that Node.js 18+ and npm are installed, and prepare a Zebrunner account and API token.
Get the code
Clone or download the project code to a local directory.
Install dependencies
Install all the dependency packages required by the project.
Configure the connection
Create a.env file and fill in your Zebrunner connection information.
Build the project
Compile the project code into an executable file.
Configure the AI assistant
Add the MCP server configuration in Claude Desktop/Code.
Start using
Restart the AI assistant and start querying test information in natural language.

Usage examples

Daily test case review by a manual QA engineer
QA engineers need to quickly review the quality and integrity of test cases to ensure that they are clear and executable.
Automation engineer generates test code
Automation engineers need to convert manual test cases into automation test code to save writing time.
Developer understands test requirements
Developers need to understand relevant test cases and requirements before implementing functions.
Test manager gets project quality report
Test managers need to understand the overall test coverage and quality status of the project.
Analyze test failure reasons
QA engineers need to quickly analyze the root causes of test failures.
Quick analysis through URL
Users can directly paste the Zebrunner URL for quick analysis.

Frequently Asked Questions

Do I need programming knowledge to use this tool?
How to obtain a Zebrunner API token?
Which AI assistants are supported?
What should I do if I encounter an "Authentication failed" error?
Can I customize the verification rules for test cases?
Will the tool affect the existing data in Zebrunner?
Which test frameworks are supported for code generation?
How to update to a new version?

Related resources

GitHub repository
Project source code and latest version
Detailed installation guide
Detailed installation steps including troubleshooting
Tool catalog
Complete list and examples of all available tools
Intelligent rule system guide
Detailed description of the three - layer intelligent rule system
Screenshot analysis guide
How to use the screenshot analysis function
Node.js download
Download the Node.js runtime environment
Model Context Protocol
Official documentation of the MCP protocol
Zebrunner official website
Zebrunner test management platform

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "mcp-zebrunner": {
      "command": "node",
      "args": ["/full/absolute/path/to/mcp-zebrunner/dist/server.js"],
      "env": {
        "ZEBRUNNER_URL": "https://your-company.zebrunner.com/api/public/v1",
        "ZEBRUNNER_LOGIN": "your.email@company.com",
        "ZEBRUNNER_TOKEN": "your_api_token_here",
        "DEBUG": "false",
        "ENABLE_RULES_ENGINE": "true",
        "DEFAULT_PAGE_SIZE": "100",
        "MAX_PAGE_SIZE": "100"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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