Zephyr MCP Server
Z

Zephyr MCP Server

An MCP server for integrating with Zephyr Scale, providing test case retrieval and filtering capabilities.
2 points
14.8K

What is the Zephyr MCP Server?

The Zephyr MCP Server is a middleware service that allows developers and testers to interact with the Zephyr Scale test management tool through the standardized Model Context Protocol. It simplifies the process of retrieving test cases from Zephyr Scale and provides flexible filtering options.

How to use the Zephyr MCP Server?

Before use, simple configuration is required, including installing dependencies, setting up the API token, and configuring VS Code. After configuration, you can retrieve test cases from Zephyr Scale with simple commands.

Use cases

Suitable for scenarios where Zephyr Scale test cases need to be integrated into the development workflow, such as automated testing, continuous integration/continuous deployment (CI/CD) processes, and seamless docking of test case management with the development environment.

Main Features

Retrieve Test Cases
Retrieve test cases from Zephyr Scale, supporting filtering by project and folder
Flexible Filtering Options
Support filtering by project key (project_key) and folder ID (folder_id)
Result Quantity Control
You can limit the number of returned test cases through the max_results parameter
Advantages
Simplifies the integration process with Zephyr Scale
Provides a standardized MCP interface, easy to integrate with other tools
Flexible filtering options can accurately retrieve the required test cases
Lightweight and easy to deploy
Limitations
Currently only supports the test case retrieval function
Requires valid Zephyr Scale API access permissions
Does not support modifying or creating test cases

How to Use

Clone the Repository
Clone the Zephyr MCP Server code repository to your local machine
Install Dependencies
Install all the required Python dependency packages for running
Configure VS Code
Add the MCP server configuration to the VS Code settings
Set the API Token
Create a .env file in the project root directory and add your Zephyr Scale API token

Usage Examples

Retrieve All Test Cases in a Project
Retrieve all test cases (up to 10) in the specified project
Retrieve Test Cases in a Specific Folder
Retrieve 5 test cases in the specified folder

Frequently Asked Questions

How to obtain the Zephyr Scale API token?
Does it support modifying or creating test cases?
How to increase the number of returned test cases?

Related Resources

Zephyr Scale Official Documentation
Official documentation and API reference for Zephyr Scale
MCP Protocol Specification
Official specification document for the Model Context Protocol
GitHub Repository
Source code for the Zephyr MCP Server

Installation

Copy the following command to your Client for configuration
{
     "mcpServers": {
       "zephyr": {
         "command": "python",
         "args": ["zephyr/zephyr.py"]
       }
     }
   }
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
8.7K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
10.4K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
15.2K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
8.1K
4 points
P
Paperbanana
Python
9.2K
5 points
F
Finlab Ai
FinLab AI is a quantitative financial analysis platform that helps users discover excess returns (alpha) in investment strategies through AI technology. It provides a rich dataset, backtesting framework, and strategy examples, supporting automated installation and integration into mainstream AI programming assistants.
10.2K
4 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
9.9K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
10.3K
5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
27.9K
4.3 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
23.4K
4.5 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
38.7K
5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
81.2K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
38.8K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
71.8K
4.5 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
24.5K
4.5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
108.1K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase