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    Mcp Jira

    JIRA integration server for Model Context Protocol (MCP) - enables LLMs to interact with JIRA tasks and workflows

    6 stars
    Python
    Updated Sep 10, 2025

    Table of Contents

    • Features
    • Core MCP Tools
    • Project Management Capabilities
    • Reliability
    • Requirements
    • Quick Setup
    • Usage Examples
    • Creating Issues
    • Sprint Management
    • Team Management
    • Daily Standups
    • MCP Integration
    • With Claude Desktop
    • With Other MCP Clients
    • Configuration
    • Required Environment Variables
    • Optional Settings
    • Getting Jira API Token
    • Architecture
    • Troubleshooting
    • Common Issues
    • Debug Mode
    • Development
    • License

    Table of Contents

    • Features
    • Core MCP Tools
    • Project Management Capabilities
    • Reliability
    • Requirements
    • Quick Setup
    • Usage Examples
    • Creating Issues
    • Sprint Management
    • Team Management
    • Daily Standups
    • MCP Integration
    • With Claude Desktop
    • With Other MCP Clients
    • Configuration
    • Required Environment Variables
    • Optional Settings
    • Getting Jira API Token
    • Architecture
    • Troubleshooting
    • Common Issues
    • Debug Mode
    • Development
    • License

    Documentation

    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

    Requirements

    • Python 3.8 or higher
    • Jira Cloud account with API token
    • MCP-compatible client (like Claude Desktop)

    Quick Setup

    1. Clone and install:

    bash
    git clone https://github.com/your-org/mcp-jira.git
    cd mcp-jira
    python3 -m venv .venv
    source .venv/bin/activate
    pip install -e .

    2. Configure Jira credentials:

    bash
    cp .env.example .env
    # Edit .env with your values
    env
    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. Test the server:

    bash
    .venv/bin/python -m mcp_jira

    You should see Initializing MCP Jira server... in the output. Press Ctrl+C to stop.

    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

    The config file is located at:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json

    Add the following entry, replacing /path/to/mcp-jira with the absolute path where you cloned the repo:

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

    Note: Use the Python binary from inside the .venv folder — this ensures all dependencies are available. The cwd field is not required; the server resolves its configuration using absolute paths internally.

    To find the correct path, run this from inside the project directory:

    bash
    echo "$(pwd)/.venv/bin/python"

    Restart Claude Desktop after saving the config.

    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:

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

    3. Run tests:

    bash
    python -m pytest tests/ -v

    4. Submit a pull request

    License

    MIT License - see LICENSE file

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