Jira MCP Server

Create a powerful Model Context Protocol (MCP) server for Jira in minutes with our AI Gateway. This guide walks you through setting up seamless Jira integration with enterprise-grade security and instant OAuth authentication.

About Jira API

Jira is the #1 software development tool used by agile teams, with over 65,000 companies relying on it for project management. The Jira API provides comprehensive access to issues, projects, workflows, and more:

• Issue Management: Create, update, transition, and manage issues
• Project Configuration: Manage projects, versions, and components
• Agile Boards: Access Scrum and Kanban boards, sprints, and backlogs
• Workflow Engine: Execute transitions, manage statuses, and automation
• JQL Queries: Advanced search using Jira Query Language
• User Management: Handle users, groups, and permissions
• Custom Fields: Access and manage custom field values
• Attachments & Comments: Full media and conversation management

Key Features

• REST API v3: Modern RESTful interface with JSON
• Cloud & Server: Support for both deployment models
• Webhooks: Real-time event notifications
• Rate Limiting: 10 requests per second for cloud
• Bulk Operations: Efficient batch processing
• Rich Text: Support for Atlassian Document Format
• App Integration: Extensive marketplace ecosystem
• Advanced Search: Powerful JQL query engine

What You Can Do with Jira MCP Server

The MCP server transforms Jira's API into a natural language interface, enabling AI agents to:

Issue Management

• Smart Issue Operations

  • "Create a bug for the login page with high priority"
  • "Move all bugs in QA to Done if they pass testing"
  • "Find all critical issues assigned to me"
  • "Update story points for all issues in current sprint"

• Bulk Issue Processing

  • "Add label 'needs-review' to all unassigned issues"
  • "Transition all approved issues to In Progress"
  • "Clone all issues from Sprint 23 to Sprint 24"
  • "Link related security issues together"

• Issue Intelligence

  • "Show me issues blocked for more than 3 days"
  • "Find stories without acceptance criteria"
  • "List bugs reported by customers this week"
  • "Identify issues with missing estimates"

Agile Management

• Sprint Operations

  • "Create a new 2-week sprint starting Monday"
  • "Move incomplete issues to the next sprint"
  • "Calculate team velocity for last 5 sprints"
  • "Show sprint burndown progress"

• Backlog Management

  • "Prioritize backlog by business value"
  • "Estimate all stories in the backlog"
  • "Create epics from related user stories"
  • "Groom backlog items older than 3 months"

• Board Automation

  • "Update board columns based on issue status"
  • "Set WIP limits for development column"
  • "Create swimlanes by issue priority"
  • "Configure quick filters for team members"

Reporting & Analytics

• Performance Metrics

  • "Generate team velocity report for Q4"
  • "Show cycle time for completed issues"
  • "Analyze bug resolution rates by component"
  • "Track SLA compliance for support issues"

• Workload Analysis

  • "Show workload distribution across team"
  • "Identify overallocated team members"
  • "Calculate story points per developer"
  • "Find bottlenecks in the workflow"

• Quality Metrics

  • "Count bugs by severity and component"
  • "Track reopened issues by reason"
  • "Measure test coverage by feature"
  • "Report on code review turnaround"

Workflow Automation

• Smart Transitions

  • "Auto-transition issues when PR is merged"
  • "Move issues to QA when build passes"
  • "Escalate blocked issues to managers"
  • "Close resolved issues after 7 days"

• Notifications & Alerts

  • "Alert PM when sprint scope changes"
  • "Notify team of new critical bugs"
  • "Send daily standup summaries"
  • "Remind assignees of due dates"

• Integration Workflows

  • "Create Jira issues from Slack messages"
  • "Sync Jira tickets with GitHub issues"
  • "Update CRM when customer issues close"
  • "Generate release notes from completed issues"

Team Collaboration

• Assignment Intelligence

  • "Assign bugs to developers by expertise"
  • "Balance workload across team members"
  • "Route customer issues to support team"
  • "Reassign issues when team members are OOO"

• Communication Enhancement

  • "Summarize issue discussions for stakeholders"
  • "Extract action items from comments"
  • "Translate technical issues for business users"
  • "Generate status updates from issue changes"

Prerequisites

• Access to Cequence AI Gateway
• Jira Cloud or Server instance
• Jira administrator access
• Ability to create OAuth apps (Atlassian account)

Step 1: Create Atlassian OAuth App

Before setting up the MCP server, you need to create an OAuth app in Atlassian.

1.1 Access Atlassian Developer Console

1. Navigate to developer.atlassian.com
2. Sign in with your Atlassian account
3. Click Create OAuth 2.0 integration

1.2 Configure OAuth App

1. Set basic information:

   • App name: "AI Gateway Jira MCP"
   • App description: "MCP server for Jira integration"
   • Company: Your organization name

2. Configure OAuth 2.0:

   • Callback URL:

     https://auth.aigateway.cequence.ai/v1/outbound/oauth/callback

3. Configure Permissions:

   • Go to Permissions tab
   • Add Jira API scopes (see Available Scopes section)

1.3 Get OAuth Credentials

1. Go to Settings tab
2. Note down:
   • Client ID
   • Client Secret (click to reveal)

1.4 Configure App Details

1. Add App logo (optional)
2. Set Privacy policy URL
3. Set Terms of service URL
4. Configure Data residency if needed

Step 2: Access AI Gateway Apps

1. Log in to your Cequence AI Gateway dashboard
2. Navigate to Apps in the left sidebar
3. You'll see the list of available third-party applications

Step 3: Find and Select Jira API

1. In the Apps section, browse through the Third-party category
2. Look for Jira or use the search function
3. Click on the Jira API card to view details

The Jira API card shows:

• Number of available endpoints
• Integration capabilities
• Quick description of functionality

Step 4: Create MCP Server

1. Click the Create MCP Server button on the Jira API card
2. You'll be redirected to the MCP Server creation wizard

Step 5: Configure API Endpoints

In the App Configuration step:

1. Base URL is pre-filled: https://your-domain.atlassian.net
2. Select API endpoints to expose to your MCP server based on your needs
3. Click Next to proceed

Step 6: MCP Server Basic Setup

Configure your MCP server details:

1. MCP Server Name: Enter a descriptive name

   • Example: "Jira Project Automation"
   • This name will identify your server in the dashboard

2. Description (Optional): Add details about the server's purpose

   • Example: "Automated Jira operations for agile project management"

3. Production Mode: Toggle based on your needs

   • ON for production environments
   • OFF for development/testing

4. Click Next to continue

Step 7: Configure Authentication

This is where you'll use your Atlassian OAuth credentials:

1. Authentication Type: Select OAuth 2.0

2. Fill in the OAuth configuration:

   • Authorization URL:

     https://auth.atlassian.com/authorize

   • Token URL:

     https://auth.atlassian.com/oauth/token

   • Client ID: Paste from Atlassian developer console
   • Client Secret: Paste from Atlassian developer console
   • Redirect URI:

     https://auth.aigateway.cequence.ai/v1/outbound/oauth/callback

3. Scopes: Select from the available Jira scopes (see next section)

Available Jira OAuth Scopes

Configure the appropriate scopes based on your application needs:

Core Access

• read:jira-user

  • View user information
  • Access user profiles and avatars
  • Read user preferences
  • List user groups

• read:jira-work

  • Read issues and projects
  • View boards and sprints
  • Access workflows and schemes
  • Read custom fields and screens

• write:jira-work

  • Create and update issues
  • Manage sprints and boards
  • Execute workflow transitions
  • Update custom field values

Project Management

• manage:jira-project

  • Create and configure projects
  • Manage project roles and permissions
  • Configure issue types and workflows
  • Archive and delete projects

• manage:jira-configuration

  • Configure Jira settings
  • Manage custom fields
  • Create workflows and schemes
  • Set up automation rules

Recommended Scope Combinations

For Issue Management:

read:jira-user
read:jira-work
write:jira-work

For Full Project Administration:

read:jira-user
read:jira-work
write:jira-work
manage:jira-project
manage:jira-configuration

For Read-Only Analytics:

read:jira-user
read:jira-work

Step 8: Configure Security

Set up API protection features:

1. API Protection: Toggle ON to enable

   • Protects against bot attacks, DDoS, and threats
   • Monitors for suspicious activity
   • Rate limiting and anomaly detection

2. Protection Features (when enabled):

   • Auto-scaling protection
   • Managed infrastructure
   • Built-in monitoring
   • Zero maintenance required

3. Click Next to continue

Step 9: Choose Deployment Method

Select your deployment preference:

Option A: Deploy to Cequence Cloud (Recommended)

• Fully managed deployment
• Automatic scaling and monitoring
• Built-in high availability
• Features included:
  • Auto-scaling
  • Managed infrastructure
  • Built-in monitoring
  • Zero maintenance

Option B: Deploy with Helm Chart

• Self-managed Kubernetes deployment
• Full control over infrastructure
• Requires:
  • Kubernetes cluster
  • Helm 3.x installed
  • Container registry access

Click Next after selecting your deployment method.

Step 10: Review and Deploy

Review your MCP server configuration:

• MCP Server Name: Your chosen name
• Base URL: https://your-domain.atlassian.net
• Selected Endpoints: Number of endpoints selected
• Authentication: OAuth 2.0 (Configured)
• API Protection: Enabled/Disabled
• Deployment: Cequence Cloud or Helm

Click Create & Deploy to finalize the setup.

Step 11: Post-Deployment Setup

After successful deployment:

1. Note the MCP Server URL provided

2. Test the OAuth flow:

   • Click "Test Connection"
   • You'll be redirected to Atlassian authorization
   • Select Jira site to authorize
   • Grant requested permissions
   • Confirm successful connection

3. Configure AI Agents:

   • The MCP server is now available for AI agent connections
   • Use the provided server URL in your AI agent configuration

Using Your Jira MCP Server

With Claude Desktop

1. Open Claude Desktop settings

2. Add your MCP server:

   {
     "servers": {
       "jira": {
         "url": "your-mcp-server-url",
         "auth": {
           "type": "oauth2",
           "client_id": "your-client-id"
         }
       }
     }
   }

3. Start using natural language commands:

   • "Show me all issues assigned to me in the current sprint"
   • "Create a bug for the payment processing error"
   • "Move all approved stories to In Progress"
   • "Generate a sprint report for the team meeting"
   • "Find all blockers in the current release"

API Integration Example

// Initialize MCP client
const mcpClient = new MCPClient({
  serverUrl: 'your-mcp-server-url',
  auth: {
    type: 'oauth2',
    token: 'user-access-token'
  }
});

// Search issues with JQL
const issues = await mcpClient.jira.search({
  jql: 'project = PROJ AND sprint in openSprints() AND assignee = currentUser()',
  fields: ['summary', 'status', 'priority']
});

// Create an issue
const newIssue = await mcpClient.jira.issues.create({
  fields: {
    project: { key: 'PROJ' },
    issuetype: { name: 'Bug' },
    summary: 'Login page returns 500 error',
    description: 'Users cannot log in due to server error',
    priority: { name: 'High' },
    assignee: { accountId: 'user-account-id' }
  }
});

// Transition an issue
await mcpClient.jira.issues.transition({
  issueIdOrKey: 'PROJ-123',
  transition: { id: '21' }, // In Progress
  fields: {
    resolution: { name: 'Fixed' }
  }
});

// Add comment
await mcpClient.jira.issues.addComment({
  issueIdOrKey: 'PROJ-123',
  body: 'Fixed in commit abc123. Ready for QA testing.'
});

Common Use Cases

Agile Development

• Sprint planning and management
• Story point estimation
• Velocity tracking
• Burndown chart generation
• Retrospective action items

Bug Tracking

• Automated bug triage
• Priority assignment
• Duplicate detection
• Resolution tracking
• Regression monitoring

Release Management

• Version planning
• Release note generation
• Feature tracking
• Deployment coordination
• Rollback procedures

Support Operations

• Ticket routing
• SLA monitoring
• Customer communication
• Escalation workflows
• Knowledge base integration

Security Best Practices

1. OAuth Security:

   • Use minimum required scopes
   • Implement token rotation
   • Store tokens securely
   • Monitor token usage

2. API Rate Limits:

   • Respect Atlassian rate limits
   • Implement request queuing
   • Use webhook events when possible
   • Cache frequently accessed data

3. Data Protection:

   • Filter sensitive information
   • Respect project permissions
   • Implement audit logging
   • Follow data residency requirements

4. Access Control:

   • Use project-based permissions
   • Implement role-based access
   • Regular permission audits
   • Monitor unusual activity

Troubleshooting

Common Issues

1. 401 Unauthorized

   • Verify OAuth token validity
   • Check Atlassian site access
   • Ensure correct permissions granted
   • Re-authenticate if needed

2. 403 Forbidden

   • Check user has Jira access
   • Verify project permissions
   • Ensure issue visibility
   • Check field-level security

3. 429 Too Many Requests

   • Atlassian rate limit: 10 req/sec
   • Implement exponential backoff
   • Use batch operations
   • Consider webhook alternatives

4. 400 Bad Request

   • Validate required fields
   • Check field formats
   • Verify workflow rules
   • Review custom field constraints

Getting Help

• Documentation: AI Gateway Docs
• Support: support@cequence.ai
• Community: AI Gateway Forum
• Jira Cloud API: developer.atlassian.com/cloud/jira
• Atlassian Support: support.atlassian.com

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