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thanhhien2510kt

QA Assistant MCP

by thanhhien2510kt
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Python
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QA Assistant MCP

A production-ready MCP (Model Context Protocol) server that gives Claude Desktop and Claude Code the ability to read Jira user stories, search Confluence documentation, and generate professional QA artifacts powered by GPT-4o.

Features

Tool

Description

get_user_story

Fetch a Jira issue with summary, description, acceptance criteria, labels, priority

search_confluence

Full-text search across Confluence pages

get_requirement_context

Merge Jira story + relevant Confluence pages into one context

generate_test_scenarios

AI-generated scenario table (ID, Scenario, Priority, Risk)

generate_test_cases

Comprehensive test cases — Positive, Negative, Boundary, Validation, Permission

generate_rtm

Requirements Traceability Matrix mapping ACs to test cases

analyze_test_coverage

Coverage %, missing areas, risk areas, recommendations

generate_test_summary

Executive report with coverage, risks, and release readiness

Related MCP server: MCP Atlassian

Prerequisites

  • Python 3.12+

  • Jira Cloud account with API token

  • Confluence Cloud account with API token

  • OpenAI API key (GPT-4o access recommended)

  • Claude Desktop or Claude Code

Installation

1. Clone the repository

git clone <your-repo-url>
cd qa-mcp

2. Create a virtual environment

python -m venv .venv

# Windows
.venv\Scripts\activate

# macOS / Linux
source .venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Configure environment variables

cp .env.example .env

Edit .env with your credentials:

JIRA_URL=https://your-domain.atlassian.net
JIRA_EMAIL=your-email@example.com
JIRA_API_TOKEN=your-jira-api-token

CONFLUENCE_URL=https://your-domain.atlassian.net
CONFLUENCE_EMAIL=your-email@example.com
CONFLUENCE_API_TOKEN=your-confluence-api-token

OPENAI_API_KEY=sk-your-openai-api-key

How to get API tokens:

Running the Server

Standalone test (stdio mode)

python server.py

Development with MCP Inspector

mcp dev server.py

Claude Desktop Configuration

Add to your Claude Desktop config file:

Windows: %APPDATA%\Claude\claude_desktop_config.json macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "qa-assistant": {
      "command": "python",
      "args": ["C:\\full\\path\\to\\qa-mcp\\server.py"],
      "env": {
        "JIRA_URL": "https://your-domain.atlassian.net",
        "JIRA_EMAIL": "your-email@example.com",
        "JIRA_API_TOKEN": "your-jira-api-token",
        "CONFLUENCE_URL": "https://your-domain.atlassian.net",
        "CONFLUENCE_EMAIL": "your-email@example.com",
        "CONFLUENCE_API_TOKEN": "your-confluence-api-token",
        "OPENAI_API_KEY": "sk-your-openai-api-key"
      }
    }
  }
}

Tip: Use the full absolute path to server.py. On Windows use double backslashes or forward slashes.

After saving, restart Claude Desktop.

Claude Code Configuration

Add to your project's .mcp.json:

{
  "mcpServers": {
    "qa-assistant": {
      "command": "python",
      "args": ["server.py"],
      "cwd": "C:\\full\\path\\to\\qa-mcp"
    }
  }
}

Or run directly:

claude mcp add qa-assistant python server.py

Usage Examples

Once connected to Claude, use natural language:

Get the user story for US-123
Search Confluence for "payment gateway BRD"
Get the full requirement context for PROJ-456
Generate test scenarios for US-123
Generate test cases for US-123
Generate RTM for US-123
Analyze test coverage for US-123
Create a test summary report for US-123

Project Structure

qa-mcp/
├── server.py                  # MCP server entry point
├── tools/
│   ├── __init__.py
│   ├── jira_tools.py          # get_user_story, get_requirement_context
│   ├── confluence_tools.py    # search_confluence
│   ├── testcase_tools.py      # generate_test_scenarios, generate_test_cases,
│   │                          #   generate_rtm, analyze_test_coverage
│   └── report_tools.py        # generate_test_summary
├── services/
│   ├── __init__.py
│   ├── jira_service.py        # Jira API wrapper (atlassian-python-api)
│   ├── confluence_service.py  # Confluence API wrapper
│   └── ai_service.py          # OpenAI GPT-4o integration
├── models/
│   ├── __init__.py
│   ├── story.py               # UserStory Pydantic model
│   └── testcase.py            # TestCase, Scenario, RTM, Coverage models
├── .env                       # Your credentials (not committed)
├── .env.example               # Template
├── requirements.txt
└── README.md

Troubleshooting

Problem

Solution

EnvironmentError: Missing Jira credentials

Check that .env is in the qa-mcp/ directory and all three Jira vars are set

AuthError from Jira/Confluence

Verify email + API token; the token is NOT your password

openai.AuthenticationError

Check OPENAI_API_KEY starts with sk-

Tool not appearing in Claude

Restart Claude Desktop after editing claude_desktop_config.json

ModuleNotFoundError

Ensure virtual environment is activated when running server.py

Notes

  • All AI generation uses GPT-4o by default. Override with OPENAI_MODEL=gpt-4o-mini for lower cost.

  • Jira and Confluence use the same Atlassian API token — same credentials work for both.

  • The server reads .env from its own directory regardless of where you invoke it.

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