Python Jira MCP
P

Python Jira MCP

A Python service implementing the MCP protocol, integrating the Jira API for AI models to call
2 points
9.5K

What is the Python Jira MCP Server?

This is a Python server based on the Model Context Protocol (MCP), specifically designed to connect AI models with the Jira project management tool. It allows AI assistants to directly query Jira issues, search for tasks, and return the results to users.

How to use the Python Jira MCP Server?

You need to configure your Jira API credentials first and then start the server. After that, AI assistants (such as Cursor) can send requests through the standard protocol to obtain Jira data.

Use cases

Suitable for development teams and project managers who need AI assistants to help query Jira task status and search for specific issues. It can be integrated into various AI development environments for use.

Main features

JQL search
Use the Jira Query Language (JQL) to search for issues that meet the criteria, supporting custom return fields and result quantity limits
Get issue details
Get the complete information of a specific Jira issue through the issue ID or Key, including summary, description, status, etc.
MCP protocol integration
Fully compatible with the Model Context Protocol standard and can seamlessly collaborate with various AI tools that support MCP
Environment configuration
Easily configure Jira API credentials through the.env file without hard - coding sensitive information
Advantages
Standardized interface: Uses the MCP protocol and is compatible with various AI tools
Function - focused: Focuses on the core functions of Jira integration and is simple and easy to use
Flexible configuration: Supports environment variable configuration and is convenient for deployment
Limitations
Limited functionality: Currently only supports query functions and does not support creating or modifying issues
Depends on the Jira API: Requires valid Jira API access permissions
Technical threshold: Requires basic knowledge of Python environment configuration

How to use

Install dependencies
Ensure that Python 3.8+ is installed, and then install the required dependency packages
Configure Jira credentials
Copy the.env.example file to.env and fill in your Jira API credentials
Start the server
Run the main program to start the MCP server
Connect AI tools
Configure the server path in tools that support MCP, such as Cursor, and start using the Jira query function

Usage examples

Query in - progress tasks
Project managers need to know all current in - progress tasks
Get issue details
Developers need to view the complete information and historical changes of a specific issue

Frequently Asked Questions

What kind of Jira permissions do I need to use this server?
Which Jira cloud versions does the server support?
How to verify that the server is running normally?
Can I query multiple Jira projects at the same time?

Related resources

Model Context Protocol official documentation
Official specifications and descriptions of the MCP protocol
Atlassian Jira API documentation
Official documentation of the Jira REST API
Python MCP SDK
Python SDK code library for the MCP protocol

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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