MCP Jira Integration

A simple Model Context Protocol (MCP) server for Jira that allows LLMs to act as project managers and personal assistants for teams using Jira. Built on the Jira REST API v3.

Features

Core MCP Tools

• create_issue - Create new Jira issues with proper formatting and ADF descriptions

• search_issues - Search issues using JQL with smart formatting and pagination

• get_sprint_status - Get comprehensive sprint progress reports with metrics

• get_team_workload - Analyze team member workloads and capacity

• generate_standup_report - Generate daily standup reports automatically

Project Management Capabilities

• Multi-Project Support: Work with multiple projects by specifying project keys dynamically

• Sprint progress tracking with visual indicators

• Team workload analysis and capacity planning

• Automated daily standup report generation

• Issue creation with proper prioritization

• Smart search and filtering of issues

Reliability

• Automatic retry with exponential backoff on rate limits (429) and transient errors (503)

• Pagination for large result sets

• Timezone-aware date handling

• Graceful handling of custom Jira statuses and issue types

Related MCP server: JIRA MCP Server

Requirements

• Python 3.8 or higher

• Jira Cloud account with API token

• MCP-compatible client (like Claude Desktop)

Quick Setup

1. Clone and install:

cd mcp-jira
python3 -m venv .venv
source .venv/bin/activate
pip install -e .

2. Configure Jira credentials in .env:

cp .env.example .env
# Edit .env with your values

JIRA_URL=https://your-domain.atlassian.net
JIRA_USERNAME=your.email@domain.com
JIRA_API_TOKEN=your_api_token
PROJECT_KEY=PROJ
DEFAULT_BOARD_ID=123

3. Run the MCP server:

python -m mcp_jira

Usage Examples

Creating Issues

"Create a high priority bug for the login system not working properly"

• Auto-assigns proper issue type, priority, and formatting

Sprint Management

"What's our current sprint status?"

• Gets comprehensive progress report with metrics and visual indicators

Team Management

"Show me the team workload for john.doe, jane.smith, mike.wilson"

• Analyzes capacity and provides workload distribution

Daily Standups

"Generate today's standup report"

• Creates formatted report with completed, in-progress, and blocked items

MCP Integration

With Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-jira": {
      "command": "/path/to/mcp-jira/.venv/bin/python",
      "args": ["-m", "mcp_jira"],
      "cwd": "/path/to/mcp-jira"
    }
  }
}

With Other MCP Clients

The server follows the standard MCP protocol and works with any MCP-compatible client.

Configuration

Required Environment Variables

• JIRA_URL - Your Jira instance URL

• JIRA_USERNAME - Your Jira username/email

• JIRA_API_TOKEN - Your Jira API token

• PROJECT_KEY - Default project key for operations (can be overridden per request)

Optional Settings

• DEFAULT_BOARD_ID - Default board for sprint operations (can be overridden per request)

• STORY_POINTS_FIELD - Custom field ID for Story Points (default: customfield_10026)

• DEBUG_MODE - Enable debug logging (default: false)

• LOG_LEVEL - Logging level (default: INFO)

Getting Jira API Token

1. Go to Atlassian Account Settings

2. Click "Create API token"

3. Give it a name and copy the token

4. Use your email as username and the token as password

Architecture

This implementation prioritizes simplicity and reliability:

• Single MCP server file - All tools in one place

• Standard MCP protocol - Uses official MCP SDK

• Jira REST API v3 - Uses Atlassian Document Format (ADF) for descriptions

• Rich formatting - Provides beautiful, readable reports

• Retry with backoff - Handles rate limits and transient Jira API errors automatically

• Pagination - Fetches all results for large issue sets

• Error handling - Graceful handling of Jira API issues and custom statuses

• Async support - Fast and responsive operations

Troubleshooting

Common Issues

1. "No active sprint found"

   • Make sure your board has an active sprint

   • Check that DEFAULT_BOARD_ID is set correctly

2. Authentication errors

   • Verify your API token is correct

   • Check that your username is your email address

3. Permission errors

   • Ensure your Jira user has appropriate project permissions

   • Check that the project key exists and you have access

Debug Mode

Set DEBUG_MODE=true in your .env file for detailed logging.

Development

1. Fork the repository

2. Set up a dev environment:

python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

3. Run tests:

python -m pytest tests/ -v

4. Submit a pull request

License

MIT License - see LICENSE file