Hosted MCP Server for Atlassian Jira

Set Up Your Atlassian Jira Environment

Create Your Atlassian Jira API Key

1. Access Atlassian Account: Log in to Atlassian Account .

2. Create API Token:

   • Select Create API token with scopes.

     

   • Give your API token a descriptive name (e.g., FlowHunt-Jira-Integration).

   • Select an expiration date for the token (1 to 365 days).

   • Click Create.

   • Select Copy to clipboard and paste the token to a secure location, such as a password manager, for use in FlowHunt.

   

💡 Pro Tip: Store your API token securely and avoid sharing it publicly. Using environment variables for API token management is recommended for enhanced security.

Connect to FlowHunt Dashboard

1. Access FlowHunt: Log in to your FlowHunt.io dashboard .

2. Navigate to Integrations: Find the “Integrations” section in the left sidebar.

3. Select Atlassian Jira: Click on the Atlassian Jira integration option to begin the setup process.

   

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Configure the Atlassian Jira Integration

Enter Connection Details

In the Atlassian Jira integration setup page, provide the following information:

Deploy the Atlassian Jira MCP Server

Add the MCP Server

1. Navigate to MCP Servers: Go to the “MCP Servers” tab in your FlowHunt dashboard.
2. Add New Server: Click “Add New MCP Server”.
3. Select Atlassian Jira: Choose “Atlassian Jira MCP Server” from the available options.
4. Enter API Details: Provide the API token and, if required, the API URL and username.
5. Configure Server Tools: Select the tools you want to enable for your MCP server.

6. Finalize Setup: Click “Add MCP Server” to complete the configuration.

📝 Note: You can modify or add tools later based on your evolving automation needs.

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Connect MCP Server to Client

Configure the MCP Client

1. Access Connect Tab: Navigate to the “Connect” tab in your MCP Server configuration.
2. Choose Client: Select your preferred MCP client:
   • FlowHunt AI Agent (recommended)
   • Claude Desktop
   • Custom client applications
3. Apply Configuration: Use the provided JSON format:

{
   "mcp": {
      "transport": "streamable_http",
      "url": "https://mcp.flowhunt.io/••••••••"
   }
}

Security Considerations

🔒 Important: Treat your MCP server URL as a password. It provides direct access to your Jira data and server tools. Never share it publicly or commit it to version control.

4. Test the Connection: Verify functionality by running a test query, such as searching issues or retrieving issue details.

Create AI-Powered Workflows

You have two powerful options for implementing your Atlassian Jira automation:

Option A: Quick Start with Preconfigured Flow

Best for: Getting started quickly with proven automation patterns

1. Generate Flow: In your MCP Server configuration, click “Create Preconfigured Flow”.

2. Select Template: Choose “AI Agent with MCP” to create a ready-to-use workflow.

3. Customize Logic: Use FlowHunt’s visual flow builder to tailor the automation:

   • Set up page creation for meeting notes or reports.
   • Configure automatic content updates for documentation.
   • Implement page searches for knowledge base queries.
   • Create automated notifications for page changes.

   

4. Activate: Save and activate your flow to begin automated operations.

Option B: Custom Integration

Best for: Specific automation requirements or existing workflow enhancement

1. Create/Edit Flow: Open FlowHunt’s flow builder and start with a new or existing flow.
2. Add MCP Component: Drag the “MCP Server Component” onto your canvas.
3. Configure Connection: Paste your MCP client configuration:

{
   "mcp": {
      "transport": "streamable_http",
      "url": "https://mcp.flowhunt.io/••••••••"
   }
}

4. Design Workflow: Create custom logic that leverages the MCP server tools:

   • Search pages for specific project documentation.
   • Update page content based on external triggers.
   • Create new pages for automated reporting.
   • Retrieve page details for AI-driven content analysis.

   

5. Deploy: Save your configuration and activate the flow.

List of Prompts

Here are practical examples demonstrating how to use the Jira MCP Server with your AI agents. These prompts showcase real-world project management scenarios:

Issue Discovery and Search

Search for all high-priority bugs in the PROJECT-123 project that are currently unassigned

Show me all issues assigned to john@company.com that are due within the next 3 days

Find all user stories in our current sprint that are still in 'In Progress' status

Issue Creation and Management

Create a new bug issue in PROJECT-123 with title 'Login page not responsive on mobile' and assign it to the frontend team

Update issue PROJECT-456 to change the priority to 'Critical' and add a comment explaining the urgency

Batch create 10 subtasks for epic PROJECT-789 based on the following requirements: [requirements list]

Move issue PROJECT-234 from 'In Progress' to 'Code Review' status

Sprint and Agile Management

List all issues in the current sprint for board ID 12 and group them by assignee

Create a new sprint called 'Q1 Feature Release' for board 45 starting next Monday and ending in two weeks

Show me the velocity report by listing completed issues from the last 3 sprints

Collaboration and Communication

Add a comment to issue PROJECT-567 mentioning @sarah that the API integration is complete and ready for testing

Get all comments on issue PROJECT-890 to review the discussion history

Add a worklog entry to PROJECT-345 for 3 hours spent on code refactoring today

Project Organization

List all versions for project PROJECT-123 and show which ones are released vs. unreleased

Create a new version called 'v2.5.0' for project PROJECT-456 with release date set to end of month

Link issue PROJECT-111 to PROJECT-222 with relationship type 'blocks' to indicate dependency

Reporting and Analytics

Download all attachments from issue PROJECT-789 and save them for documentation purposes

Search for all issues created in the last 30 days that have priority 'High' or 'Critical' across all projects

These prompts demonstrate how Jira MCP integration enables efficient project management, from issue tracking and sprint planning to team collaboration and reporting workflows.

Conclusion

Integrating Atlassian Jira MCP Server with FlowHunt.io creates a powerful foundation for intelligent project management automation. Whether you’re streamlining issue tracking, automating sprint management, or enhancing team collaboration, this integration empowers your AI agents to work seamlessly with your critical Jira data.

Start with a simple automation and gradually expand your workflows as you become more comfortable with the platform. The combination of Jira’s robust project management capabilities and FlowHunt’s AI-driven automation will transform how your team collaborates and delivers projects.

Ready to get started? Begin your integration today and unlock the full potential of AI-powered project management automation!