Enables fetching and manipulating data from CucumberStudio (a Cucumber.io product), providing context about projects, features, and scenarios, and allowing AI to generate and modify test scenarios and other CucumberStudio resources.
Supports configuration through environment variables, allowing secure storage of API tokens and server settings.
Provides the runtime environment for the MCP server, requiring Node.js v18+ for operation.
Offers package management for installing dependencies and running the server.
Provides an alternative package management option for installing dependencies and running the server.
CucumberStudio MCP Server
This project implements a Model Context Protocol (MCP) server for CucumberStudio API. It provides context from the CucumberStudio platform to AI-powered applications, enabling various AI operations to be performed with CucumberStudio data.
Overview
The Model Context Protocol server enables AI assistants to:
Fetch data from CucumberStudio API
Provide context about CucumberStudio projects, features, scenarios, and other resources
Enable AI to generate and modify test scenarios, features, and other CucumberStudio resources
Related MCP server: MCP Server Demo
Setup
Prerequisites
Node.js (v18+)
npm or yarn
CucumberStudio API token
Installation
Clone this repository
Install dependencies:
npm installor
yarn installCreate a
.envfile in the root directory with the following content:CUCUMBER_STUDIO_API_TOKEN=your_api_token_here PORT=3000
Running the Server
To start the server:
or
API Endpoints
The MCP server exposes the following endpoints:
GET /context: Fetch context from CucumberStudioPOST /apply: Apply changes to CucumberStudio resourcesGET /schema: Get the schema for the MCP server
Implementation Details
This MCP server follows the Model Context Protocol specification and integrates with the CucumberStudio API available at https://studio-api.cucumberstudio.com/.
License
MIT