Install
$ agentstack add mcp-mallikarjun-roddannavar-ai-testcase-generator-mcp ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
🤖 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 (
stdiotransport). - 📝 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
ai-testcase-designer-mcp/
├── build/ # Compiled JavaScript output
├── assets/ # Demo gifs, images, and sample files
│ ├── demo.gif
│ ├── excel_preview.png
│ └── sample_chat_message.txt
├── configs/
│ └── config.json # Server/tool config
├── src/
│ ├── index.ts # Main server entry point (MCP interface & routing)
│ ├── excel.ts # Excel file creation & writing logic (modular)
│ ├── logger.ts # Winston logger configuration & log writing (modular)
│ └── prompts/
│ └── testcase_prompt.txt # Prompt template for LLM-based test generation
├── package.json
├── tsconfig.json
├── README.md
└── .gitignore
- src/excel.ts: Handles all Excel (.xlsx) file creation and test plan export (modularized).
- src/logger.ts: Provides modular logging functionality across the MCP server using Winston.
- src/prompts/: Contains prompt templates for LLM-driven test generation.
- assets/: Demo GIFs, Excel sample preview, and chat prompt examples.
🎥 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:
- Clone the repository
``bash git clone https://github.com/yourusername/ai-testcase-designer-mcp.git cd ai-testcase-designer-mcp ``
- Install dependencies
``bash npm install ``
- Build the server
``bash npm run build ``
- Configure the server in your MCP client
#### a. Claude Desktop or any MCP-compatible client
- Add the following server configuration:
- On MacOS:
~/Library/Application Support/Claude/claude_desktop_config.json
- On Windows:
%APPDATA%/Claude/claude_desktop_config.json
``json { "mcpServers": { "ai-testcase-designer-mcp": { "disabled": false, "timeout": 60, "command": "node", "args": [ "c:/Auto_WS/ai-testcase-designer-mcp/build/index.js" ], "transportType": "stdio" } } } ``
#### b. Cline (VS Code Extension)
You can also use the AI Testcase Designer MCP server with Cline, the Model Context Protocol VS Code extension.
Quick Start:
- Install Cline from the VS Code Marketplace.
- Open the Cline sidebar (from the VS Code activity bar).
- Go to the "MCP Servers" section and click "Add New MCP Server".
- Fill in the server details:
``json { "mcpServers": { "ai-testcase-designer-mcp": { "disabled": false, "timeout": 60, "command": "node", "args": [ "c:/Auto_WS/ai-testcase-designer-mcp/build/index.js" ], "transportType": "stdio" } } } ``
- Test the connection and save.
For a visual step-by-step guide, see below:
For detailed Cline guidance, see the official docs: cline.bot/getting-started/installing-cline#vs-code-marketplace%3A-step-by-step-setup
c. Hermes Agent
You can also use the AI Testcase Designer MCP server with Hermes Agent.
- Add the following server configuration to
~/.hermes/config.yamlundermcp_servers:
mcp_servers:
ai-testcase-designer-mcp:
command: "node"
args: ["/absolute/path/to/ai-testcase-designer-mcp/build/index.js"]
🔑 API Key & Work Directory Setup
To use the AI Testcase Designer MCP.
- Get your Groq API key from here for free: https://console.groq.com/keys
- 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
- 🖥️ Open Claude Desktop (or any MCP-compatible client).
- 📂 Download Sample Chat Message: [samplechatmessage.txt](./assets/samplechatmessage.txt) and copy its content.
- ✉️ Paste the content into the chat and send the message: the AI will generate detailed test cases in Excel format.
- 💾 Generated Excel files and server logs are saved in your
WORK_DIRfolder.
▶️ Example Request
{
"name": "generate_tests_excel",
"arguments": {
"endpoint": "https://api.example.com/v1/users",
"method": "POST",
"payload": {
"name": "John Doe",
"email": "john@example.com"
},
"extraContext": "Focus on invalid email and empty payload scenarios."
}
}
📊 Example Excel Output
| Sl no | Test Name | Pre-Condition | Steps | Expected Result | |-------|-------------------|---------------|-------------------------------------|---------------------------| | 1 | Valid User Create | DB is empty | Send POST with valid payload | User created successfully | | 2 | Missing Email | DB is empty | Send POST with name only | 400 validation error | | 3 | Invalid Email | DB is empty | Send POST with invalid email format | 422 error message |
📂 Files Output
Files are written to: ./workdir/generated/
Sample Log Output
2025-09-13T10:22:11 [info]: [Step1] Incoming request: endpoint=/v1/users, method=POST
2025-09-13T10:22:11 [info]: [Step2] Building LLM prompt...
2025-09-13T10:22:13 [info]: [Step5] Converting LLM JSON to Excel rows (15 test cases)
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: Mallikarjun-Roddannavar
- Source: Mallikarjun-Roddannavar/ai-testcase-generator-mcp
- License: MIT
Install and usage instructions live in the source repository linked above.
Reviews
No reviews yet — be the first.
Write a review
Versions
- v0.1.0 Imported from the upstream source.