Python Jira MCP Server

Integrations

  • Supports loading Jira credentials from environment variables using python-dotenv for secure configuration.

  • Integrates with Atlassian's Jira API, enabling AI models to perform Jira operations like searching for issues and retrieving issue details.

  • Provides tools for searching Jira issues with JQL queries and retrieving detailed information about specific Jira issues, including fields like summary, description, status, and assignee.

Python Jira MCP Server

A Model Context Protocol (MCP) server implementation in Python that integrates with Jira API. This allows AI models to interact with Jira through a standardized protocol.

Overview

This MCP server exposes Jira API operations as tools that can be used by AI models supporting the Model Context Protocol. The server implements the stdio transport mechanism to communicate with clients like Cursor.

Features

  • JQL Search Tool: Search for Jira issues using JQL queries
  • Get Issue Tool: Retrieve detailed information about a specific Jira issue
  • MCP SDK Integration: Compatible with the official MCP Python SDK
  • Fallback Mode: Minimal implementation when the SDK is not available
  • Environment Configuration: Load Jira credentials from environment variables

Requirements

  • Python 3.8+
  • Jira API access (API token, email, and domain)
  • Required Python packages:
    • mcp (Model Context Protocol Python SDK)
    • aiohttp (for HTTP requests)
    • pydantic (for validation)
    • python-dotenv (for environment variables)

Installation

  1. Clone this repository:
    git clone https://github.com/yourusername/python-jira-mcp.git cd python-jira-mcp
  2. Install the dependencies:
    pip install -r requirements.txt
  3. Set up your Jira credentials:
    cp .env.example .env # Edit .env with your Jira credentials

Usage

Running the Server

To start the MCP server, run:

python main.py

Or use the executable directly:

./main.py

The server will start and listen for MCP messages on standard input (stdin) and respond on standard output (stdout).

Integrating with Cursor

To use this MCP server with Cursor:

  1. Start the server (as above)
  2. In Cursor, configure the MCP server path to point to main.py
  3. Use Jira tools directly within Cursor

Available Tools

Search for Jira issues using JQL (Jira Query Language).

Example:

{ "type": "tool_call", "id": "123", "name": "jql_search", "parameters": { "jql": "project = XYZ AND status = 'In Progress'", "max_results": 10, "fields": ["summary", "description", "status"] } }
Get Issue

Retrieve details about a specific Jira issue by its ID or key.

Example:

{ "type": "tool_call", "id": "456", "name": "get_issue", "parameters": { "issue_id_or_key": "XYZ-123", "fields": ["summary", "description", "status", "assignee"], "expand": "changelog" } }

Development

Project Structure

  • main.py: Entry point for the MCP server
  • src/server.py: Main MCP server implementation
  • src/tools/jira_tools.py: Jira API tool implementations
  • src/tool_schemas.py: Tool schemas definition

Adding New Tools

To add a new Jira-related tool:

  1. Implement the tool function in src/tools/jira_tools.py
  2. Add the tool schema in src/tool_schemas.py
  3. Register the tool in src/server.py

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

-
security - not tested
F
license - not found
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

A server implementation that allows AI models to interact with Jira through the Model Context Protocol, enabling tasks like JQL searches and retrieving issue details.

  1. Overview
    1. Features
      1. Requirements
        1. Installation
          1. Usage
            1. Running the Server
            2. Integrating with Cursor
            3. Available Tools
          2. Development
            1. Project Structure
            2. Adding New Tools
          3. License
            1. Acknowledgments

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