Enterprise DNA
M MCP Servers Developer low

TamarEngel/jira-github-mcp

by Various

A Model Context Protocol (MCP) server exposing Jira and GitHub actions as AI tools to streamline developer workflows end-to-end.

T

MCP

TamarEngel/jira-github-mcp

Added 1 June 2026

Overview

A Model Context Protocol (MCP) server that exposes Jira and GitHub actions as tools for AI agents. It enables developers to query, create, and update Jira issues and GitHub repositories via natural language commands from an MCP-compatible assistant.

Best for

Best for
Developers who want to control Jira and GitHub through an MCP-compatible AI assistant

Use cases

  • Automate Jira issue creation and status updates from an AI chat
  • Query GitHub repository information and pull requests through an agent
  • Link Jira tasks to GitHub branches or commits using natural language

Notes

A Model Context Protocol (MCP) server that exposes Jira and GitHub actions as tools for AI agents. It enables developers to query, create, and update Jira issues and GitHub repositories via natural language commands from an MCP-compatible assistant.

1 stars on GitHub. Last updated 2026-01-09. Licensed MIT.

Use cases

  • Automate Jira issue creation and status updates from an AI chat
  • Query GitHub repository information and pull requests through an agent
  • Link Jira tasks to GitHub branches or commits using natural language

Pros

  • Directly integrates two major project management and code hosting platforms
  • Open source Python implementation is easy to customize or extend
  • Works with any MCP-compatible AI client, not tied to a specific provider

Cons

  • Very low community adoption (1 star) means limited real-world testing
  • Requires local server setup and an MCP-enabled AI client to be useful
  • Documentation likely minimal due to early stage

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Directly integrates two major project management and code hosting platforms
  • Open source Python implementation is easy to customize or extend
  • Works with any MCP-compatible AI client, not tied to a specific provider

Cons

  • Very low community adoption (1 star) means limited real-world testing
  • Requires local server setup and an MCP-enabled AI client to be useful
  • Documentation likely minimal due to early stage