QA MCP Test Case Generator

QA MCP Test Case Generator

An AI-powered QA Test Case Generator built using Python, FastMCP, GitHub Models API, and Excel Reporting.

This project demonstrates how the Model Context Protocol (MCP) can be used to build AI-powered QA assistants that automatically read software requirements and generate:

• Test Scenarios
• Manual Test Cases
• Requirement Traceability Matrix (RTM)
• Risk Analysis
• Test Data
• Excel Reports

---

Project Overview

Traditional AI applications directly access files using Python.

This project demonstrates a real MCP architecture, where the application communicates with a Filesystem MCP Server to retrieve requirement documents.

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Project Architecture

                    QA Engineer
                         │
                         ▼
                 main.py (Host)
                         │
                         ▼
                 MCP Client
                         │
                Python STDIO Transport
                         │
                         ▼
             Filesystem MCP Server
                         │
                         ▼
             Requirement Documents
                         │
                         ▼
               GitHub Models API
                         │
                         ▼
          AI Generated QA Artifacts
                         │
                         ▼
             Excel Workbook Output

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Project Structure

QA_MCP_TestCase_Generator

│
├── main.py
├── mcp_client.py
├── github_models_client.py
├── prompts.py
├── excel_generator.py
├── .env
│
├── mcp_servers
│   └── filesystem_server.py
│
├── requirements
│   ├── LoginRequirement.txt
│   ├── RegistrationRequirement.txt
│   └── PaymentRequirement.txt
│
└── output

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Features

✔ Filesystem MCP Server

✔ MCP Client

✔ Tool Discovery

✔ Requirement Reader

✔ AI-powered Test Scenario Generation

✔ AI-powered Test Case Generation

✔ AI-powered RTM Generation

✔ AI-powered Risk Analysis

✔ AI-powered Test Data Generation

✔ Excel Workbook Generation

---

MCP Tools

The Filesystem MCP Server exposes the following tools:

Tool	Description
list_requirement_files()	Lists all available requirement files
read_requirement_file()	Reads a requirement document
generate_test_scenarios()	Generates test scenarios
generate_test_cases()	Generates detailed manual test cases
generate_rtm()	Generates Requirement Traceability Matrix
generate_risks()	Generates QA risk analysis
generate_test_data()	Generates test data

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Technologies Used

• Python 3.12+
• FastMCP
• GitHub Models API
• OpenAI Python SDK
• Pandas
• OpenPyXL
• dotenv

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Prerequisites

Install:

• Python 3.12+
• Git
• Visual Studio Code
• GitHub Account

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Clone Repository

git clone https://github.com/<your-username>/qa-mcp-testcase-generator.git

cd qa-mcp-testcase-generator

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Create Virtual Environment

Windows

python -m venv .venv

Activate

.venv\Scripts\activate

Mac/Linux

python3 -m venv .venv

source .venv/bin/activate

---

Install Dependencies

pip install -r requirements.txt

or

pip install fastmcp

pip install openai

pip install pandas

pip install openpyxl

pip install python-dotenv

---

Configure GitHub Models API

Create a .env file in the project root.

Example

GITHUB_TOKEN=your_github_models_api_key

---

Add Requirement Files

Place all requirement documents inside:

requirements/

Example:

LoginRequirement.txt

RegistrationRequirement.txt

PaymentRequirement.txt

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Start the Application

python main.py

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Main Menu

====================================================
QA Filesystem MCP Assistant
====================================================

1. Show Available MCP Tools

2. List Requirement Files

3. Read Requirement File

4. Generate Test Scenarios

5. Generate Test Cases

6. Generate RTM

7. Generate Risks

8. Generate Test Data

9. Generate Complete QA Workbook

0. Exit

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Output

Generated files are saved inside

output/

Example

QA_Workbook.xlsx

Scenarios.xlsx

TestCases.xlsx

RTM.xlsx

Risks.xlsx

TestData.xlsx

---

Example Workflow

User selects

↓

RegistrationRequirement.txt

↓

Filesystem MCP Server reads file

↓

GitHub Models API analyzes requirement

↓

AI generates

• Test Scenarios

• Test Cases

• RTM

• Risks

• Test Data

↓

Excel Workbook created

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MCP Concepts Demonstrated

✔ MCP Server

✔ MCP Client

✔ Tool Discovery

✔ Tool Invocation

✔ Python STDIO Transport

✔ AI Integration

✔ Prompt Engineering

✔ Enterprise QA Automation

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Future Enhancements

• Jira MCP Server
• Browser MCP Server
• Database MCP Server
• Playwright MCP Server
• API Testing MCP Server
• Complete QA Sprint Agent
• HTML Dashboard
• PDF Report Generation
• Multi-Agent Workflow
• Docker Support

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Learning Outcomes

After exploring this project, you'll understand how to:

• Build a custom MCP Server using FastMCP
• Expose custom QA tools
• Connect an MCP Client to a Filesystem MCP Server
• Integrate GitHub Models API with MCP
• Generate AI-powered QA artifacts
• Export AI-generated outputs to Excel
• Design enterprise-ready AI-assisted QA workflows

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Contributions

Contributions are welcome!

Feel free to:

• Report bugs
• Suggest improvements
• Raise issues
• Submit Pull Requests

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If you found this project helpful...

Please consider giving this repository a ⭐ on GitHub.

It helps others discover the project and motivates future enhancements.

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Author

Neelam Pal

QA Architect | AI in Testing | MCP | Agentic AI | Test Automation | Quality Engineering

Connect with me on LinkedIn to explore more AI-powered QA projects and tutorials.