MCP Jira Integration
by Warzuponus
This project integrates Claude AI with Jira to automate and enhance project management tasks. It uses the MCP protocol for standardized interactions.
Last updated: N/A
What is MCP Jira Integration?
This is a Python-based integration that allows AI assistants to interact with Jira using the MCP (Message Communication Protocol). It provides a standardized way to create, manage, and search Jira issues through AI.
How to use MCP Jira Integration?
- Clone the repository. 2. Configure environment variables in
.env
with your Jira URL, username, API token, project key, and a secure API key for MCP authentication. 3. Use the provided Python code snippets to create and search issues via the MCP protocol. 4. Integrate with an AI assistant that supports the MCP protocol by configuring the MCP endpoint.
Key features of MCP Jira Integration
Jira issue creation and management through MCP protocol
API key-based authentication
Standardized request/response format for AI interactions
Issue creation and updates
Basic sprint tracking
Project and board management
Issue search and retrieval
Use cases of MCP Jira Integration
Automated issue creation based on AI analysis of user requests
AI-powered issue updates and task assignments
Intelligent issue search and retrieval using natural language queries
Integration with AI assistants for voice-controlled Jira management
FAQ from MCP Jira Integration
What is MCP?
What is MCP?
MCP stands for Message Communication Protocol, a standardized way for AI assistants and applications to communicate.
How do I get a Jira API token?
How do I get a Jira API token?
You can create an API token in your Atlassian account settings under 'Security' -> 'API Tokens'.
What Python version is required?
What Python version is required?
Python 3.8 or higher is required.
How do I configure the API key?
How do I configure the API key?
Set the API_KEY
environment variable in the .env
file with a secure API key.
Can I contribute to this project?
Can I contribute to this project?
Yes, you can fork the repository, create a feature branch, and submit a pull request.