mcp-server-atlassian-jira

mcp-server-atlassian-jira

4
developer_toolscommunication

The Atlassian Jira MCP Server is a Node.js/TypeScript server that enables secure and real-time interaction between AI systems and Atlassian Jira Cloud. It is designed for comprehensive and efficient data retrieval using a standardized Model Context Protocol (MCP), allowing integration with AI assistants.

Atlassian Jira MCP Server

A Node.js/TypeScript Model Context Protocol (MCP) server for Atlassian Jira Cloud. Enables AI systems to securely interact with your Jira projects, issues, comments, and related development information in real time.

Why Use This Server?

  • Minimal Input, Maximum Output: Simple identifiers provide comprehensive details.
  • Complete Jira Context: Access projects, issues, comments, and metadata.
  • Rich Development Information: Insights into branches, commits, and pull requests linked to issues.
  • Secure Local Authentication: Run locally with credentials, no remote token storage.
  • Intuitive Markdown Responses: Consistent formatting for outputs.

What is MCP?

Model Context Protocol (MCP) is an open standard for securely connecting AI systems to tools and data sources, enabling AI assistants to interact with Jira programmatically.

Setup

  1. Generate Atlassian API token.
  2. Configure credentials using either MCP config file or environment variables.
  3. Install and run using npx or global npm package.
  4. Connect to AI assistant with MCP-compatible clients.

MCP Tools

Commands for interacting with Jira such as listing projects, getting project details, searching issues, viewing issue details and comments, and adding comments.

CLI Commands

  • ls-projects: List Jira projects.
  • get-project: Get project details.
  • ls-issues: Search for issues.
  • get-issue: Get issue details.
  • ls-comments: List comments.
  • add-comment: Add a comment.

Response Format

All responses are Markdown-formatted with structured data, pagination info, and related resource links.

Development

Clone the repository, install dependencies, and run in development mode or test it. Contributions are welcome through pull requests.