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securityF
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qualityA server implementation that allows AI models to interact with Jira through the Model Context Protocol, enabling tasks like JQL searches and retrieving issue details.
Last updated -
The JIRA MCP Server provides access to JIRA data with relationship tracking, optimized payloads, and data cleaning for AI contexts. It supports both Jira Cloud and Jira Server (Data Center) instances.
Key capabilities:
Search JIRA issues using JQL (max 50 results per request)
Retrieve epic children including comments and relationships (max 100 issues per request)
Get detailed issue information with comments and relationships
Create new JIRA issues with specified fields
Update existing JIRA issue fields
Add file attachments to JIRA issues (using Base64 encoded content)
Add comments to JIRA issues (converting plain text to Atlassian Document Format)
Get available status transitions for a JIRA issue
Change the status of a JIRA issue by performing a transition
Clean and transform JIRA content for AI efficiency
Track issue relationships (mentions, links, parent/child, epics)
Provides access to JIRA data including searching issues, retrieving epic children, getting detailed issue information, creating and updating issues, extracting issue mentions, tracking issue relationships, handling file attachments, and transforming JIRA content for AI context windows
JIRA MCP Server
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
Jira Cloud & Jira Server (Data Center) Support
This MCP server supports both Jira Cloud and Jira Server (Data Center) instances. You can select which type to use by setting the JIRA_TYPE environment variable:
cloud(default): For Jira Cloud (Atlassian-hosted)server: For Jira Server/Data Center (self-hosted)
The server will automatically use the correct API version and authentication method for the selected type.
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
Add comments to 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
Supports both Jira Cloud and Jira Server (Data Center) APIs
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
JIRA_TYPE=cloud # or 'server' for Jira Server/Data Center (optional, defaults to 'cloud')
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.jsonClaude Desktop:
~/Library/Application Support/Claude/claude_desktop_config.json
Windows:
Cline:
%APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.jsonClaude Desktop:
%APPDATA%\Claude Desktop\claude_desktop_config.json
Linux:
Cline:
~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.jsonClaude Desktop: sadly doesn't 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",
"JIRA_TYPE": "cloud"
}
}
}
}
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
}
add_comment
Add a comment to a JIRA issue. Accepts plain text and converts it to the required Atlassian Document Format internally.
Input Schema:
{
issueIdOrKey: string, // The ID or key of the issue to add the comment to
body: string // The content of the comment (plain text)
}
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.
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