Customer JIRA Tracker

A comprehensive JIRA ticket tracking system with MCP (Model Context Protocol) integration for Cursor IDE. This system allows you to track customer-specific JIRA tickets with full CRUD operations and seamless integration with Cursor's AI assistant.

🚀 Features

• Customer Management: Create and manage customer profiles
• Ticket Tracking: Add, remove, and track JIRA tickets per customer
• Comment System: Add comments to individual tickets
• Export Functionality: Export customer data to Markdown format with JIRA integration
• MCP Integration: Direct integration with Cursor IDE via MCP protocol
• Dual Deployment: Support for both local development and OpenShift production
• Flexible Authentication: API key-based authentication with SSL verification control

🏗️ Architecture

The system consists of three main components:

1. HTTP API Server (local_http_server.py / OpenShift deployment)

• FastAPI-based REST API
• Customer and ticket management endpoints
• JSON file-based data storage
• API key authentication

1. MCP Server (mcp_server.py)

• Bridges Cursor IDE to the HTTP API
• Exposes MCP tools for customer and ticket operations
• Handles SSL verification for different environments
• Supports both local and OpenShift deployments

1. Cursor Integration (cursor-mcp-config.json)

• Configuration for Cursor IDE
• Environment-specific settings
• SSL verification control

🚀 Quick Start

Prerequisites

• Podman (for containerized deployment)
• Cursor IDE

1. Clone and Setup

git clone <repository-url>
cd jiraTracker

2. Configure MCP Integration

#### Option A: Interactive Setup (Recommended)

./setup_mcp.sh

The interactive setup will prompt you for:

• JIRA Personal Token
• GitHub Personal Access Token
• OpenShift API URL
• OpenShift API Key
• SSL verification settings for both local and OpenShift environments

#### Option B: Manual Configuration

cp cursor-mcp-config.template.json ~/.cursor/mcp.json
# Edit ~/.cursor/mcp.json with your specific values

3. Start the Services

#### Containerized Local Development (Recommended)

./run_local.sh

This will:

• Build the HTTP API server container
• Build the MCP server container
• Start the HTTP API server
• Configure MCP to use containerized services

4. Restart Cursor IDE

After configuration, restart Cursor to load the MCP servers.

📊 Export Functionality

The Customer JIRA Tracker includes powerful export capabilities to generate Markdown reports of customer ticket data.

Export Features

• Markdown Format: Clean, readable Markdown tables
• JIRA Integration: Optional JIRA data (Status, Priority, Assignee, Last Updated)
• Customer Summary: Total tickets, comments, and last updated information
• Comments Section: Detailed ticket comments with timestamps
• File Storage: Automatic saving to customer data directory

Export API Endpoint

GET /api/customers/{customer_name}/export

Parameters:

• format (default: "markdown") - Export format
• include_jira (default: false) - Include JIRA information
• save_file (default: true) - Save to file in customer data directory

Example Usage:

# Basic export
curl "http://localhost:8080/api/customers/AA/export"

# Export with JIRA data
curl "http://localhost:8080/api/customers/AA/export?include_jira=true"

# Export without saving to file
curl "http://localhost:8080/api/customers/AA/export?save_file=false"

MCP Tool Usage

In Cursor IDE, use the export_customer_data tool:

{
  "customer_name": "AA",
  "format": "markdown",
  "include_jira": true,
  "save_file": true
}

Export Output Example

# Customer: AA

**Last Updated:** 2025-10-02T11:40:36.101729
**Total Tickets:** 2
**Total Comments:** 1

## Notes
Initial ticket for AA customer

## Tickets

| Ticket Key | Added Date | Comments | Status | Priority | Assignee | Last Updated |
| --- | --- | --- | --- | --- | --- | --- |
| `RFE-1234` | 2025-10-02 | 1 | N/A (MCP Integration Pending) | N/A (MCP Integration Pending) | N/A (MCP Integration Pending) | N/A (MCP Integration Pending) |

## Comments

### RFE-1234
**2025-10-02T11:38:25**

This is a test comment for the export functionality

🔧 Configuration

Environment Variables

MCP Server Configuration

The MCP server supports two deployment modes using containerized services:

#### Local Development (Containerized)

{
  "customer-jira-tracker-local": {
    "command": "podman",
    "args": [
      "run", "-i", "--name=customer-jira-tracker-client",
      "--network=host",
      "-e", "CUSTOMER_JIRA_API_URL=http://localhost:8080",
      "-e", "CUSTOMER_JIRA_API_KEY=local-dev-key",
      "-e", "CUSTOMER_JIRA_SSL_VERIFY=false",
      "localhost/customer-jira-tracker-client:local"
    ],
    "env": {
      "CUSTOMER_JIRA_API_URL": "http://localhost:8080",
      "CUSTOMER_JIRA_API_KEY": "local-dev-key",
      "CUSTOMER_JIRA_SSL_VERIFY": "false"
    }
  }
}

#### OpenShift Production (Containerized)

{
  "customer-jira-tracker-openshift": {
    "command": "podman",
    "args": [
      "run", "-i", "--name=customer-jira-tracker-client-openshift",
      "-e", "CUSTOMER_JIRA_API_URL=https://customer-jira-tracker-server.apps.your-domain.com",
      "-e", "CUSTOMER_JIRA_API_KEY=your-production-key",
      "-e", "CUSTOMER_JIRA_SSL_VERIFY=true",
      "quay.io/your-org/customer-jira-tracker-client:latest"
    ],
    "env": {
      "CUSTOMER_JIRA_API_URL": "https://customer-jira-tracker-server.apps.your-domain.com",
      "CUSTOMER_JIRA_API_KEY": "your-production-key",
      "CUSTOMER_JIRA_SSL_VERIFY": "true"
    }
  }
}

🔐 Authentication & Security

Local Development

• Default: No authentication required
• Optional: Set CUSTOMER_JIRA_API_KEY for API key authentication
• SSL: Not required for local development

OpenShift Production

• Required: API key authentication via CUSTOMER_JIRA_API_KEY
• SSL: HTTPS required, but verification can be disabled for self-signed certificates
• Security: Use strong, unique API keys

SSL Verification Control

The CUSTOMER_JIRA_SSL_VERIFY environment variable controls SSL certificate verification:

• "true" (default): Verify SSL certificates (recommended for production)
• "false": Skip SSL verification (useful for self-signed certificates in development)

📚 Available MCP Tools

Once configured, the following tools are available in Cursor:

Customer Management

• list_customers - List all customers with ticket counts
• get_customer_tickets - Get all tickets for a specific customer

Ticket Operations

• add_customer_tickets - Add tickets to a customer
• remove_customer_tickets - Remove tickets from a customer
• add_ticket_comment - Add a comment to a specific ticket

Customer Updates

• update_customer_notes - Update customer notes

🛠️ Development

Project Structure

jiraTracker/
├── Dockerfile                # Main container image (OpenShift HTTP server)
├── Dockerfile.mcp            # MCP server container image
├── mcp_server.py             # MCP server implementation
├── local_http_server.py      # HTTP API server (for local development)
├── cursor-mcp-config.json    # Cursor MCP configuration
├── cursor-mcp-config.template.json  # Template for manual setup
├── setup_mcp.sh             # Interactive setup script
├── run_local.sh             # Local development runner (containerized)
├── openshift/               # OpenShift deployment files
│   ├── http_server.py       # OpenShift HTTP server
│   ├── deployment.yaml      # Kubernetes deployment
│   └── ...
└── customer_jira_data/      # JSON data storage

Container Images

The project uses two main container images:

1. HTTP API Server (customer-jira-tracker-server:local)

• Based on Dockerfile.server
• Runs the HTTP API server
• Used for both local development and OpenShift production

1. MCP Client (customer-jira-tracker-client:local)

• Based on Dockerfile.client
• Runs the MCP server that bridges to the HTTP API
• Used by Cursor IDE for MCP integration

Building Container Images

# Build HTTP API server image
podman build -t customer-jira-tracker-server:local -f Dockerfile.server .

# Build MCP client image
podman build -t customer-jira-tracker-client:local -f Dockerfile.client .

# Build for OpenShift production
podman build -t quay.io/your-org/customer-jira-tracker-server:latest -f Dockerfile.server .

🚀 Deployment

Local Development (Containerized)

1. Run ./run_local.sh to start HTTP API server container
2. MCP server runs automatically when Cursor connects
3. Configure MCP with local settings (done automatically by setup script)
4. Restart Cursor IDE

OpenShift Production

1. Deploy using the provided OpenShift manifests
2. Build and push container images to your registry
3. Configure MCP with production settings
4. Set CUSTOMER_JIRA_SSL_VERIFY=false for self-signed certificates (default is true)
5. Restart Cursor IDE

🔍 Troubleshooting

Common Issues

1. MCP Tools Not Available

• Ensure Cursor is restarted after configuration
• Check ~/.cursor/mcp.json syntax
• Verify MCP server is running

1. SSL Certificate Errors

• Set CUSTOMER_JIRA_SSL_VERIFY=false for self-signed certificates (default is true)
• Ensure HTTPS URL is used for OpenShift

1. API Connection Errors

• Verify CUSTOMER_JIRA_API_URL is correct
• Check if HTTP API server is running
• Validate API key authentication

1. Validation Errors

• Ensure MCP server returns content directly (not wrapped in CallToolResult)
• Check MCP protocol compatibility

Debug Mode

# Check container status
podman ps -a

# View HTTP API server logs
podman logs customer-jira-tracker-local

# Test API connectivity
curl -H "Authorization: Bearer your-api-key" http://localhost:8080/api/customers

# Test MCP server manually
echo '{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "test-client", "version": "1.0.0"}}}' | podman run --rm -i -e CUSTOMER_JIRA_API_URL=http://host.containers.internal:8080 -e CUSTOMER_JIRA_API_KEY=local-dev-key -e CUSTOMER_JIRA_SSL_VERIFY=false localhost/customer-jira-tracker-client:local

📄 License

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

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

📞 Support

For issues and questions:

1. Check the troubleshooting section
2. Review the USAGE_GUIDE.md for detailed instructions
3. Open an issue in the repository