Jira MCP server

Jira is the leading software development and project management tool used by thousands of companies. An AI agent with access to Jira can create and manage issues, organize work in sprints, generate reports, automate workflows, and coordinate team efforts without manual Jira operations.

Setting up an MCP server

This article covers the standard steps for creating an MCP server in AI Gateway and connecting it to an AI client. The steps are the same for every integration — application-specific details (API credentials, OAuth endpoints, and scopes) are covered in the individual application pages.

Before you begin

You'll need:

• Access to AI Gateway with permission to create MCP servers
• API credentials for the application you're connecting (see the relevant application page for what to collect)

Create an MCP server

Find the API in the catalog

1. Sign in to AI Gateway and select MCP Servers from the left navigation.
2. Select New MCP Server.
3. Search for the application you want to connect, then select it from the catalog.

Configure the server

1. Enter a Name for your server — something descriptive that identifies both the application and its purpose (for example, "Zendesk Support — Prod").
2. Enter a Description so your team knows what the server is for.
3. Set the Timeout value. 30 seconds works for most APIs; increase to 60 seconds for APIs that return large payloads.
4. Toggle Production mode on if this server will be used in a live workflow.
5. Select Next.

Configure authentication

Enter the authentication details for the application. This varies by service — see the Authentication section of the relevant application page for the specific credentials, OAuth URLs, and scopes to use.

Configure security

1. Set any Rate limits appropriate for your use case and the API's own limits.
2. Enable Logging if you want AI Gateway to record requests and responses for auditing.
3. Select Next.

Deploy

Review the summary, then select Deploy. AI Gateway provisions the server and provides a server URL you'll use when configuring your AI client.

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Connect to an AI client

Once your server is deployed, you'll need to add it to the AI client your team uses. Select your client for setup instructions:

• Claude Desktop
• Claude Code
• Cursor
• VS Code
• Windsurf

Tips

• You can create multiple MCP servers for the same application — for example, a read-only server for reporting agents and a read-write server for automation workflows.
• If you're unsure which OAuth scopes to request, start with the minimum read-only set and add write scopes only when needed. Most application pages include scope recommendations.
• You can edit a server's name, description, timeout, and security settings after deployment without redeploying.

Authentication

Jira uses OAuth 2.0 authentication. Create an OAuth 2.0 integration at developer.atlassian.com and configure the redirect URI for your AI Gateway. The authorization endpoint is https://auth.atlassian.com/authorize and the token endpoint is https://auth.atlassian.com/oauth/token. Configure scopes based on your needs: read:jira-user (read user profiles), read:jira-work (read issues and boards), write:jira-work (create and update issues), manage:jira-project (manage projects), and manage:jira-configuration (manage workflows and fields). The API base URL is https://your-domain.atlassian.net.

Available tools

This MCP server enables issue management, sprint operations, reporting, and workflow automation for Jira projects across your organization.

Tool	Description
Create issue	Create a new issue with type, summary, and description
Get issue	Retrieve issue details including status and history
Update issue	Modify issue fields like status, assignee, or priority
Delete issue	Remove an issue from the system
List issues	Retrieve issues with JQL queries and filtering
Add comment	Add a comment to an issue
Add attachment	Attach files to an issue
Transition issue	Move an issue to a new workflow state
Link issue	Create links between related issues
Create subtask	Create a subtask within a parent issue
Get project	Retrieve project details and configuration
List projects	Retrieve all projects you have access to
Create sprint	Create a new sprint in a board
Get sprint	Retrieve sprint details and assigned issues
Move issue to sprint	Assign an issue to a sprint
Complete sprint	Close a sprint and move incomplete issues
List sprints	Retrieve sprints for a project
Get board	Retrieve board configuration and swimlanes
List boards	Retrieve boards for a project
Create milestone	Create a version or release milestone
Get milestone	Retrieve milestone details
Create epic	Create an epic for organizing work
Add to epic	Link issues to an epic
Create label	Create a label for organizing issues
Generate report	Create sprint velocity or burndown reports

Tips

Use Jira Query Language (JQL) for powerful searches that filter issues by any combination of fields.

Learn JQL syntax to create precise queries and avoid over-fetching data from the Jira instance.

Use the field ID not the label when updating custom fields, as field IDs are the stable identifier across workspace changes.

Get field IDs from the issue schema or Jira configuration page to ensure you're targeting the right custom field.

Check available transitions before attempting to move an issue to a new status, as not all status transitions are valid in every workflow.

Verify your project's field configuration to identify which custom fields are available and required.

Use the correct custom field ID for story points — story point estimation isn't a standard field, and the field ID varies by project.

Verify permissions before attempting sprint operations — only issue assignees or project admins can move issues between sprints.

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