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mallikarjun-roddannavar/ai-testcase-generator-mcp

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An Model Context Protocol(MCP) server that generates comprehensive API test cases (positive, negative, edge cases) from endpoint metadata, powered by AI/LLMs

Overview

An that generates comprehensive (positive, negative, and boundary/edge cases) directly from endpoint metadata—powered by . This is a TypeScript-based Model Context Protocol(MCP) server for QA engineers. It demonstrates core Model Context Protocol concepts by providing: - AI-powered tool for generating exhaustive test case plans from API endpoints and payloads - Prompt-driven LLM integration for quality and coverage - Extensible structure for future automation tooling - 🔌 (stdio transport). - 📝 Tool: generate_tests_excel - Input: endpoint, HTTP method, payload, extra context. - : - : endpoint, HTTP method, payload - Use extraContext to provide any additional testing notes or constraints - : 📊 with columns: Sl no, Test Name, Pre-Condition, Steps, Expected Result. - 🧠 with configurable LLM (Groq, OpenAI, Anthropic). - 📜 Detailed logging with . - : Handles all Excel (.xlsx) file creation and test plan export (modularized).

README

🤖 AI Testcase Generator MCP

An Model Context Protocol(MCP) server that generates comprehensive API test plans (positive, negative, and boundary/edge cases) directly from endpoint metadata—powered by LLMs.

This is a TypeScript-based Model Context Protocol(MCP) server for QA engineers. It demonstrates core Model Context Protocol concepts by providing:

  • AI-powered tool for generating exhaustive test case plans from API endpoints and payloads
  • Prompt-driven LLM integration for quality and coverage
  • Extensible structure for future automation tooling

✨ Features

  • 🔌 MCP-compliant server (stdio transport).
  • 📝 Tool: generate_tests_excel
    • Input: endpoint, HTTP method, payload, extra context.
    • Input options:
      • Direct endpoint details: endpoint, HTTP method, payload
      • Use extraContext to provide any additional testing notes or constraints
    • OutputPut: 📊 Excel test plan with columns: Sl no, Test Name, Pre-Condition, Steps, Expected Result.
  • 🧠 Prompt-driven test generation with configurable LLM (Groq, OpenAI, Anthropic).
  • 📜 Detailed logging with Winston.

🏗️ Architecture

flowchart TD
    A[Claude / MCP Client] -->|Run Tool| B[MCP Server]
    B -->|Prompt| C[LLM API]
    C -->|Test Cases JSON| B
    B -->|Excel Export| D[(Test Plan .xlsx)]
    B -->|Logs| E[Server Log File]

📂 Project Structure

🎥 Demo

Here’s the MCP generating test cases and exporting to Excel:

🔍 Excel Preview

Below is a quick preview of the generated test cases:

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

⚙️ Installation

Follow these steps to set up the AI Testcase Designer MCP server locally:

  1. Clone the repository

    git clone https://github.com/yourusername/ai-testcase-designer-mcp.git
    cd ai-testcase-designer-mcp
    
  2. Install dependencies

    npm install
    
  3. Build the server

    npm run build
    
  4. Configure the server in your MCP client

    a. Claude Desktop or any MCP-compatible client

    b. Cline (VS Code Extension)

c. Hermes Agent

🔑 API Key & Work Directory Setup

To use the AI Testcase Designer MCP.

  1. Get your Groq API key from here for free: https://console.groq.com/keys
  2. A working directory (WORK_DIR) where generated Excel test plans and server logs will be saved.

Update your config.json file like this:

{
  "MODEL_API_KEY": "gsk_7Ma3Fabcd ",
  "WORK_DIR": "C:/Auto_WS/ai-testcase-designer-mcp"
}

How to Use

  1. 🖥️ Open Claude Desktop (or any MCP-compatible client).
  2. 📂 Download Sample Chat Message: sample_chat_message.txt and copy its content.
  3. ✉️ Paste the content into the chat and send the message: the AI will generate detailed test cases in Excel format.
  4. 💾 Generated Excel files and server logs are saved in your WORK_DIR folder.

▶️ Example Request

{
  "name": "generate_tests_excel",
  "arguments": {
    "endpoint": "https://api.example.com/v1/users",
    "method": "POST",
    "payload": {
      "name": "John Doe",
      "email": "[email protected]"
    },
    "extraContext": "Focus on invalid email and empty payload scenarios."
  }
}

📊 Example Excel Output

📂 Files Output

Files are written to: ./workdir/generated/


Sample Log Output

Debugging

License

This project is licensed under the MIT License.
See the LICENSE file for details.

View the full README on GitHub

Install

This server does not publish a one-line install command.

Open the repository installation guide New to MCP? Start with the mcpskill.org guide →

Configuration

{ "mcpServers": { "ai-testcase-designer-mcp": { "disabled": false, "timeout": 60, "command": "node", "args": [ "c:/Auto_WS/ai-testcase-designer-mcp/build/index.js" ], "transportType": "stdio" } } }