JIRA

Connect QDrant Loader to JIRA to index project tickets, issues, requirements, and project management data. This guide covers setup for both JIRA Cloud and JIRA Data Center.

🎯 What Gets Processed

When you connect to JIRA, QDrant Loader can process:

Issue content - Summaries, descriptions, and comments
Issue metadata - Status, priority, assignee, labels, components
Attachments - Files attached to issues (when enabled)
Project information - Project descriptions and metadata

🔧 Authentication Setup

JIRA Cloud

API Token (Recommended)

Create an API Token: - Go to Atlassian Account Settings - Click "Create API token" - Give it a descriptive name like "QDrant Loader" - Copy the token
Set environment variables:

export JIRA_TOKEN=your_api_token_here
export JIRA_EMAIL=your-email@company.com

JIRA Data Center

Personal Access Token

Create a Personal Access Token: - Go to JIRA → Settings → Personal Access Tokens - Click "Create token" - Set appropriate permissions: READ for projects and issues - Copy the token
Set environment variables:

export JIRA_TOKEN=your_personal_access_token

⚙️ Configuration

Basic Configuration

global:
  qdrant:
    url: "http://localhost:6333"
    collection_name: "documents"
  llm:
    provider: "openai"
    base_url: "https://api.openai.com/v1"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "text-embedding-3-small"
      chat: "gpt-4o-mini"
    embeddings:
      vector_size: 1536

projects:
  my-project:
    sources:
      jira:
        my-jira:
          base_url: "https://your-domain.atlassian.net"
          deployment_type: "cloud"
          project_key: "PROJ"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"
          download_attachments: true

Advanced Configuration

global:
  qdrant:
    url: "http://localhost:6333"
    collection_name: "documents"
  llm:
    provider: "openai"
    base_url: "https://api.openai.com/v1"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "text-embedding-3-small"
      chat: "gpt-4o-mini"
    embeddings:
      vector_size: 1536

projects:
  my-project:
    sources:
      jira:
        my-jira:
          base_url: "https://your-domain.atlassian.net"
          deployment_type: "cloud"
          project_key: "PROJ"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"

          # Rate limiting
          requests_per_minute: 60
          page_size: 50

          # Attachment handling
          download_attachments: true

          # Issue filtering
          issue_types:
            - "Story"
            - "Epic"
            - "Bug"
            - "Task"
          include_statuses:
            - "To Do"
            - "In Progress"
            - "Done"

          # File conversion (requires global file_conversion config)
          enable_file_conversion: true

Multiple JIRA Instances

global:
  qdrant:
    url: "http://localhost:6333"
    collection_name: "documents"
  llm:
    provider: "openai"
    base_url: "https://api.openai.com/v1"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "text-embedding-3-small"
      chat: "gpt-4o-mini"
    embeddings:
      vector_size: 1536

projects:
  my-project:
    sources:
      jira:
        # Production JIRA Cloud
        prod-jira:
          base_url: "https://company.atlassian.net"
          deployment_type: "cloud"
          project_key: "PROD"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"

        # Development JIRA Data Center
        dev-jira:
          base_url: "https://dev-jira.company.com"
          deployment_type: "datacenter"
          project_key: "DEV"
          token: "${DEV_JIRA_TOKEN}"

🎯 Configuration Options

Validator Requirements

email + token required for deployment_type: cloud
token required for deployment_type: datacenter
requests_per_minute default: 60
page_size default: 100
Empty issue_types / include_statuses means all

Connection Settings

Option	Type	Description	Default
`base_url`	string	JIRA base URL	Required
`deployment_type`	string	Deployment type: "cloud", "datacenter", or "server"	`"cloud"`
`project_key`	string	Project key to process	Required
`token`	string	API token or Personal Access Token	Required
`email`	string	Email (required for Cloud)	Required for Cloud

Processing Settings

Option	Type	Description	Default
`requests_per_minute`	int	Rate limit for API calls	`60`
`page_size`	int	Number of issues per API request	`100`
`download_attachments`	bool	Download and process issue attachments	`false`
`enable_file_conversion`	bool	Enable file conversion for attachments	`false`

Issue Filtering

Option	Type	Description	Default
`issue_types`	list	Issue types to include	All types
`include_statuses`	list	Issue statuses to include	All statuses

🚀 Usage Examples

Software Development Team

global:
  qdrant:
    url: "http://localhost:6333"
    collection_name: "dev-docs"
  llm:
    provider: "openai"
    base_url: "https://api.openai.com/v1"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "text-embedding-3-small"
      chat: "gpt-4o-mini"
    embeddings:
      vector_size: 1536

projects:
  development:
    sources:
      jira:
        dev-project:
          base_url: "https://company.atlassian.net"
          deployment_type: "cloud"
          project_key: "DEV"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"

          # Focus on active work
          issue_types:
            - "Story"
            - "Epic"
            - "Bug"
            - "Task"
          include_statuses:
            - "To Do"
            - "In Progress"
            - "In Review"
            - "Done"

          # Include attachments for documentation
          download_attachments: true
          enable_file_conversion: true

Product Management

global:
  qdrant:
    url: "http://localhost:6333"
    collection_name: "product-docs"
  llm:
    provider: "openai"
    base_url: "https://api.openai.com/v1"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "text-embedding-3-small"
      chat: "gpt-4o-mini"
    embeddings:
      vector_size: 1536

projects:
  product:
    sources:
      jira:
        product-backlog:
          base_url: "https://company.atlassian.net"
          deployment_type: "cloud"
          project_key: "PROD"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"

          # Focus on planning items
          issue_types:
            - "Epic"
            - "Story"
            - "Initiative"

          # Include all content for context
          download_attachments: true
          enable_file_conversion: true

Support Team

global:
  qdrant:
    url: "http://localhost:6333"
    collection_name: "support-docs"
  llm:
    provider: "openai"
    base_url: "https://api.openai.com/v1"
    api_key: "${LLM_API_KEY}"
    models:
      embeddings: "text-embedding-3-small"
      chat: "gpt-4o-mini"
    embeddings:
      vector_size: 1536

projects:
  support:
    sources:
      jira:
        support-tickets:
          base_url: "https://company.atlassian.net"
          deployment_type: "cloud"
          project_key: "SUP"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"

          # Support-focused issue types
          issue_types:
            - "Bug"
            - "Support Request"
            - "Incident"
            - "Problem"

          # Include customer communications
          download_attachments: true

🧪 Testing and Validation

Initialize and Configure

# Initialize workspace
qdrant-loader init --workspace .

# Configure the project
qdrant-loader config --workspace .

Validate Configuration

# Validate project configuration
qdrant-loader config --workspace .

# Check project status
qdrant-loader config --workspace .

# List all projects
qdrant-loader config --workspace .

Process JIRA Data

# Process all configured sources
qdrant-loader ingest --workspace .

# Process specific project
qdrant-loader ingest --workspace . --project my-project

# Process with verbose logging
qdrant-loader ingest --workspace . --log-level debug

🔧 Troubleshooting

Common Issues

Authentication Failures

Problem: 401 Unauthorized or 403 Forbidden Solutions:

# Test API token manually
curl -u "your-email@company.com:your-api-token" \
  "https://your-domain.atlassian.net/rest/api/2/myself"

# Check project permissions
curl -u "your-email@company.com:your-api-token" \
  "https://your-domain.atlassian.net/rest/api/2/project"

# For Data Center, test with Personal Access Token
curl -H "Authorization: Bearer your-token" \
  "https://jira.company.com/rest/api/2/myself"

Project Access Issues

Problem: Project not found or No permission to access project Solutions:

# List accessible projects
curl -u "your-email:your-token" \
  "https://your-domain.atlassian.net/rest/api/2/project" | jq '.[].key'

# Check specific project permissions
curl -u "your-email:your-token" \
  "https://your-domain.atlassian.net/rest/api/2/project/PROJ"

Rate Limiting

Problem: 429 Too Many Requests Solutions:

projects:
  my-project:
    sources:
      jira:
        my-jira:
          base_url: "https://company.atlassian.net"
          deployment_type: "cloud"
          project_key: "PROJ"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"

          # Reduce request rate
          requests_per_minute: 30
          page_size: 25

Large Project Performance

Problem: Processing takes too long or times out

Solutions:

projects:
  my-project:
    sources:
      jira:
        my-jira:
          base_url: "https://company.atlassian.net"
          deployment_type: "cloud"
          project_key: "PROJ"
          token: "${JIRA_TOKEN}"
          email: "${JIRA_EMAIL}"

          # Optimize processing
          download_attachments: false
          page_size: 25
          requests_per_minute: 30

          # Filter to reduce scope
          issue_types:
            - "Story"
            - "Bug"
          include_statuses:
            - "Open"
            - "In Progress"

Debugging Commands

# Check JIRA API version
curl -u "email:token" "https://domain.atlassian.net/rest/api/2/serverInfo"

# List issues in a project
curl -u "email:token" \
  "https://domain.atlassian.net/rest/api/2/search?jql=project=PROJ&maxResults=5" | \
  jq '.issues[].key'

# Check issue details
curl -u "email:token" \
  "https://domain.atlassian.net/rest/api/2/issue/PROJ-123"

📊 Monitoring and Performance

Check Processing Status

# Check project status
qdrant-loader config --workspace .

# Check specific project
qdrant-loader config --workspace . --project-id my-project

# List all projects
qdrant-loader config --workspace .

Performance Optimization

Monitor these aspects for JIRA processing:

Issues processed per minute - Processing throughput
API request rate - Requests per second to JIRA
Error rate - Percentage of failed issue requests
Attachment download time - Time to download and process files
Memory usage - Peak memory during processing

🔄 Best Practices

Project Organization

Use descriptive project keys - Make projects easy to identify
Organize with components - Use components for categorization
Apply consistent labeling - Use labels for cross-project categorization
Archive completed projects - Move old projects to archive status

Performance Best Practices

Filter issue types - Process only relevant issue types
Limit attachment processing - Set download_attachments: false for large projects
Use appropriate page sizes - Balance between API calls and memory usage
Respect rate limits - Configure requests_per_minute appropriately

Security Considerations

Use API tokens - Prefer tokens over passwords
Limit token scope - Grant minimal necessary permissions
Rotate tokens regularly - Update tokens periodically
Monitor access - Track which projects are being accessed

Data Quality

Maintain consistent issue types - Use standard issue type schemes
Use structured descriptions - Follow description templates
Regular data cleanup - Archive or close old issues

File Conversion - Processing JIRA attachments
Configuration Reference - Complete configuration options
Troubleshooting - Common issues and solutions
MCP Server - Using processed JIRA content with AI tools

Ready to connect your JIRA instance? Start with the basic configuration above and customize based on your project structure and workflow needs.