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MCP Jira Integration

@Warzuponus

基本情報

カテゴリ

バージョン管理

ライセンス

MIT

トランスポート

stdio

作者

Warzuponus

MCP Jira Integration について

JIRA integration server for Model Context Protocol (MCP) - enables LLMs to interact with JIRA tasks and workflows

MCP Jira Integration の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-jira-warzuponus": {
      "command": "python3",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

MCP Jira Integration のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Jira Integration?

MCP Jira Integration is a Model Context Protocol server that connects LLMs to Jira via the Jira REST API v3. It enables AI assistants to act as project managers and personal assistants for Jira teams by providing tools like issue creation, sprint tracking, and standup generation.

How to use MCP Jira Integration?

Clone the repository, install dependencies in a virtual environment, and configure Jira credentials in a .env file. Run the server with python -m mcp_jira and connect it to any MCP-compatible client (e.g., Claude Desktop) by adding the server entry to the client’s configuration file.

Key features of MCP Jira Integration

  • Create Jira issues with proper ADF formatting
  • Search issues using JQL with pagination
  • Get comprehensive sprint progress reports
  • Analyze team member workloads and capacity
  • Generate automated daily standup reports
  • Automatic retry with exponential backoff on errors

Use cases of MCP Jira Integration

  • Create a prioritized bug or task directly from an LLM prompt
  • Ask for real-time sprint status with visual metrics
  • Review team workload distribution and capacity planning
  • Generate daily standup reports with completed and blocked items
  • Manage multiple Jira projects by specifying project keys dynamically

よくある質問

1

What are the requirements to run MCP Jira Integration?

Python 3.8 or higher, a Jira Cloud account with an API token, and an MCP-compatible client like Claude Desktop.

2

How do I get a Jira API token?

Go to Atlassian Account Settings > Security > API tokens, create a token, and use your email as username with the token as password.

3

Where do I configure the server for Claude Desktop?

The config file is at `~/Library/Application Support/Claude/claude_desktop_config.json` on macOS and `%APPDATA%\Claude\claude_desktop_config.json` on Windows. Add the server entry with the absolute path to the Python binary inside the project’s `.venv` folder.

4

What should I do if I get “No active sprint found”?

Ensure your Jira board has an active sprint and that `DEFAULT_BOARD_ID` is set correctly in your configuration.

5

Can I override the default project key per request?

Yes. The `PROJECT_KEY` and `DEFAULT_BOARD_ID` values can be overridden dynamically when calling the tools.

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