taskmaster-mcp

taskmaster-mcp

MCP server providing Jira tools to fetch, create, update tickets, manage attachments, and generate AI-powered ticket content.

Category
访问服务器

README

taskmaster-mcp

A TypeScript MCP server that gives Claude, Cursor and other MCP hosts a set of Jira tools. Built on FastMCP + Express. This is a trimmed-down version of something we actually run internally.

Treat this as your first week on the team: get it running, poke around, find something worth improving, and ship it as a pull request.

We haven't told you what to build. Deciding that is part of the exercise.


1. Make your own copy

Use the template — don't fork.

  1. On the repo page, click Use this template → Create a new repository.
  2. Name it whatever you like.
  3. Set the visibility to Private.
  4. Create the repository.

Then add @laurence-barry and @dave-r-cintra as collaborators: your repo → Settings → Collaborators → Add people.

2. Get a Jira instance

You'll need your own Jira Cloud site — the free tier takes about five minutes and doesn't need a card.

  1. Sign up at atlassian.com/software/jira/free.
  2. Create a project. A Scrum template gives you a backlog and sprint board, which next_jira_task expects. Note the project key (e.g. PROJ).
  3. Generate an API token at id.atlassian.com/manage-profile/security/api-tokens.

Spend a couple of minutes creating issues with a mix of types, statuses and priorities, plus a subtask and an epic link. Several tools walk those relationships and an empty board won't show you much.

3. Run it

Requires Node 22+.

npm install
cp example.env .env        # fill in your Jira values
npm run dev                # http://localhost:3000
JIRA_API_URL=https://your-domain.atlassian.net
JIRA_EMAIL=the-email-you-signed-up-with@example.com
JIRA_API_TOKEN=<token from step 3 above>
JIRA_PROJECT=<your project key, e.g. PROJ>
ALLOW_UNAUTHENTICATED_LOCAL=true

Four tools call Claude for ticket content — add ANTHROPIC_API_KEY from console.anthropic.com if you want those. The others work without it.

Connect an MCP client

Point the client at http://localhost:3000/mcp.

Claude Code:

claude mcp add --transport http taskmaster http://localhost:3000/mcp

Cursor — in .cursor/mcp.json:

{
  "mcpServers": {
    "taskmaster": {
      "url": "http://localhost:3000/mcp"
    }
  }
}

With ALLOW_UNAUTHENTICATED_LOCAL=true, localhost requests use your .env credentials. Try the tools out properly before you write any code — most of what's interesting here only shows up once you've used the thing.

curl -s http://localhost:3000/health

4. Build something

Pick a feature or improvement you think the project should have, and implement it.

Good choices tend to be things you noticed while using it — a rough edge, a gap in the tool coverage, something that broke when you fed it real data. We're more interested in a small, well-judged, complete change than a large half-finished one.

Work in a branch and open a pull request against main in your own repo. Don't merge it — leave it open for us to review.

Your PR description should cover

  • What you built, briefly.
  • Why you chose it over the other things you noticed.
  • Trade-offs you made, and anything you'd do differently with more time.

This matters as much as the code. A short, clear write-up beats a long one.


What we're looking for

Judgement Did you pick something that genuinely improves the project, and can you say why?
Craft Does the change fit the codebase's existing patterns and conventions?
Communication Does the PR explain itself to someone who wasn't there?
Tool use How well do you work with AI — steering it, checking it, rejecting it?

We won't be scoring you on the size of the diff.


推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选