JIRA MCP Server (Async)
@judexzhu
JIRA MCP Server (Async) について
A high-performance, asynchronous Model Context Protocol (MCP) server that integrates with JIRA using stdio transport
基本情報
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-judexzhu": {
"command": "uv",
"args": [
"sync"
]
}
}
}ツール
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概要
What is JIRA MCP Server (Async)?
A high-performance, asynchronous Model Context Protocol (MCP) server that integrates with JIRA using stdio transport. It allows AI assistants to perform JIRA operations—search, create, update issues, and track relationships—via MCP tools. Designed for developers using MCP clients like Claude Desktop.
How to use JIRA MCP Server (Async)?
Install with uv sync, configure environment variables JIRA_SERVER_URL and JIRA_API_TOKEN, then add the server to your MCP client’s configuration (e.g., Claude Desktop’s mcpServers block). The server runs over stdio and exposes tools with jira_ prefixes.
Key features of JIRA MCP Server (Async)
- 8 MCP tools covering search, read, and write operations
- Asynchronous, non-blocking API calls with connection pooling
- Built-in rate limiting to respect JIRA API limits
- Uses stdio transport for MCP client integration
- Environment variables for timeouts, logging, and concurrency
- Clean, tool-focused architecture without MCP resources
Use cases of JIRA MCP Server (Async)
- Search JIRA issues with JQL from an AI assistant
- Retrieve detailed issue information, comments, and links
- Create new issues or update existing ones programmatically
- Track epics, subtasks, and workflow transitions
FAQ from JIRA MCP Server (Async)
What JIRA operations does the server support?
The server provides tools for searching issues (jira_search_issues), getting details (jira_get_issue_details), reading comments and links, managing epics/subtasks, viewing transitions, and creating/updating issues—all with a jira_ tool prefix.
What environment variables are required?
JIRA_SERVER_URL (your JIRA instance URL) and JIRA_API_TOKEN are required. Optional variables include MAX_CONCURRENT_REQUESTS (default 2), REQUEST_TIMEOUT (30s), LOG_LEVEL, and more.
What transport does the server use?
It uses stdio transport, optimized for MCP client integration. No HTTP endpoints are exposed; the server communicates over standard input/output.
What are the runtime dependencies?
Python 3.13+ and the uv package manager. The server uses aiohttp for async HTTP calls and implements built-in connection pooling and rate limiting.
Are there any known limitations?
Rate limiting is built-in; the default MAX_CONCURRENT_REQUESTS value is 2 (requests per second). The server does not expose MCP resources—only tools—and relies entirely on the provided API token for authentication.
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