jira mcp

A Model Context Protocol (MCP) server implementation that provides access to JIRA data with relationship tracking, optimized data payloads, and data cleaning for AI context windows.

ℹ️ There is a separate MCP server for Confluence

Features

• Search JIRA issues using JQL (maximum 50 results per request)
• Retrieve epic children with comment history and optimized payloads (maximum 100 issues per request)
• Get detailed issue information including comments and related issues
• Create, update, and manage JIRA issues
• Extract issue mentions from Atlassian Document Format
• Track issue relationships (mentions, links, parent/child, epics)
• Clean and transform rich JIRA content for AI context efficiency
• Support for file attachments with secure multipart upload handling

Prerequisites

• Bun (v1.0.0 or higher)
• JIRA account with API access

Environment Variables

JIRA_API_TOKEN=your_api_token
JIRA_BASE_URL=your_jira_instance_url  # e.g., https://your-domain.atlassian.net
JIRA_USER_EMAIL=your_email

Installation & Setup

1. Clone the repository:

git clone [repository-url]
cd jira-mcp

2. Install dependencies and build:

bun install
bun run build

3. Configure the MCP server:

Edit the appropriate configuration file:

macOS: - Cline: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json - Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: - Cline: %APPDATA%CodeUserglobalStoragesaoudrizwan.claude-devsettingscline_mcp_settings.json - Claude Desktop: %APPDATA%Claude Desktopclaude_desktop_config.json

Linux: - Cline: ~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json - Claude Desktop: sadly does not exist yet

Add the following configuration under the mcpServers object:

{
  "mcpServers": {
    "jira": {
      "command": "node",
      "args": ["/absolute/path/to/jira-mcp/build/index.js"],
      "env": {
        "JIRA_API_TOKEN": "your_api_token",
        "JIRA_BASE_URL": "your_jira_instance_url",
        "JIRA_USER_EMAIL": "your_email"
      }
    }
  }
}

4. Restart the MCP server.

Within Cline's MCP settings, restart the MCP server. Restart Claude Desktop to load the new MCP server.

Development

Run tests:

bun test

Watch mode for development:

bun run dev

To rebuild after changes:

bun run build

Available MCP Tools

search_issues

Search JIRA issues using JQL. Returns up to 50 results per request.

Input Schema:

{
  searchString: string // JQL search string
}

get_epic_children

Get all child issues in an epic including their comments and relationship data. Limited to 100 issues per request.

Input Schema:

{
  epicKey: string // The key of the epic issue
}

get_issue

Get detailed information about a specific JIRA issue including comments and all relationships.

Input Schema:

{
  issueId: string // The ID or key of the JIRA issue
}

create_issue

Create a new JIRA issue with specified fields.

Input Schema:

{
  projectKey: string, // The project key where the issue will be created
  issueType: string, // The type of issue (e.g., "Bug", "Story", "Task")
  summary: string, // The issue summary/title
  description?: string, // Optional issue description
  fields?: { // Optional additional fields
    [key: string]: any
  }
}

update_issue

Update fields of an existing JIRA issue.

Input Schema:

{
  issueKey: string, // The key of the issue to update
  fields: { // Fields to update
    [key: string]: any
  }
}

add_attachment

Add a file attachment to a JIRA issue.

Input Schema:

{
  issueKey: string, // The key of the issue
  fileContent: string, // Base64 encoded file content
  filename: string // Name of the file to be attached
}

Data Cleaning Features

• Extracts text from Atlassian Document Format
• Tracks issue mentions in descriptions and comments
• Maintains formal issue links with relationship types
• Preserves parent/child relationships
• Tracks epic associations
• Includes comment history with author information
• Removes unnecessary metadata from responses
• Recursively processes content nodes for mentions
• Deduplicates issue mentions

Technical Details

• Built with TypeScript in strict mode
• Uses Bun runtime for improved performance
• Vite for optimized builds
• Uses JIRA REST API v3
• Basic authentication with API tokens
• Batched API requests for related data
• Optimized response payloads for AI context windows
• Efficient transformation of complex Atlassian structures
• Robust error handling
• Rate limiting considerations
• Maximum limits:
• Search results: 50 issues per request
• Epic children: 100 issues per request
• Support for multipart form data for secure file attachments
• Automatic content type detection and validation

Error Handling

The server implements a comprehensive error handling strategy:

• Network error detection and appropriate messaging
• HTTP status code handling (especially 404 for issues)
• Detailed error messages with status codes
• Error details logging to console
• Input validation for all parameters
• Safe error propagation through MCP protocol
• Specialized handling for common JIRA API errors
• Base64 validation for attachments
• Multipart request failure handling
• Rate limit detection
• Attachment parameter validation

LICENCE

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