📌Overview

Purpose: To integrate Claude AI with Jira for automating and improving project management tasks.

Overview: The MCP Jira Integration project enables seamless communication between Claude AI and Jira, facilitating automation of various project management functions through a standardized protocol. This integration streamlines issue handling and enhances overall project tracking.

Key Features:

Jira Issue Management: Automate the creation and management of Jira issues via the MCP protocol, allowing users to efficiently handle projects without manual input.
Sprint Tracking: Provides basic features for tracking sprints, helping teams to manage their workflows and monitor progress effectively.
Project and Board Management: Enables comprehensive management of projects and boards, ensuring that tasks and resources are organized and accessible.
Search and Retrieval: Facilitates the easy search and retrieval of issues, allowing users to quickly access relevant information and maintain productivity.

MCP Jira Integration

This project integrates Claude AI with Jira to automate and enhance project management tasks.

Features

Core Functionality

Jira issue creation and management through MCP protocol
API key-based authentication
Standardized request/response format for AI interactions

Jira Integration Features

Issue creation and updates
Basic sprint tracking
Project and board management
Issue search and retrieval

Requirements

Python 3.8 or higher
Jira account with API token
Valid MCP implementation

Setup

Clone the repository

Configure environment variables in .env:

JIRA_URL=https://your-domain.atlassian.net
JIRA_USERNAME=your.email@domain.com
JIRA_API_TOKEN=your_api_token
PROJECT_KEY=PROJ
API_KEY=your_secure_api_key  # For MCP authentication

API Usage

Create Issue

from mcp_jira.protocol import MCPRequest, MCPContext

# Create request context
context = MCPContext(
    conversation_id="conv-123",
    user_id="user-123",
    api_key="your_api_key"
)

# Create issue request
request = MCPRequest(
    function="create_issue",
    parameters={
        "summary": "Implement feature X",
        "description": "Detailed description",
        "issue_type": "Story",
        "priority": "High"
    },
    context=context
)

response = await mcp_handler.process_request(request)

Search Issues

request = MCPRequest(
    function="search_issues",
    parameters={
        "jql": "project = PROJ AND status = 'In Progress'"
    },
    context=context
)

response = await mcp_handler.process_request(request)

Authentication

All requests require an API key in the request header:

headers = {
    "X-API-Key": "your_api_key"
}

Integration with AI Assistants

This MCP implementation is designed to work with AI assistants that support the MCP protocol:

Configure the environment variables
Set up the MCP endpoint in your AI assistant's configuration
Use the standardized MCP protocol for Jira interactions

Contributing

Fork the repository
Create a feature branch
Submit a pull request

License

MIT License

mcp-jira