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Teamwork.com AI MCP Server

@rafaeljusto

基本信息

分类

其他

许可证

MIT

传输方式

stdio

作者

rafaeljusto

关于 Teamwork.com AI MCP Server

Teamwork.com extra AI capabilities

Teamwork.com AI MCP Server 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块,请前往代码仓库查看安装说明。

代码仓库

Teamwork.com AI MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Teamwork.com AI?

Teamwork.com AI is an unofficial extension for Teamwork.com that integrates AI capabilities. It includes an Assigner webservice that processes Teamwork.com webhooks to automatically extract skills and job roles from tasks and assign the best user to fulfill them. The MCP server component has been moved to the official Teamwork.com repository.

How to use Teamwork.com AI?

For the Assigner, set it up as a webservice that integrates with Teamwork.com webhooks to handle task creation and updates. For detailed instructions, refer to the assigner documentation. The MCP server is now available from the official Teamwork.com repository.

Key features of Teamwork.com AI

  • Unofficial integration with Teamwork.com
  • Assigner behaves as an Agentic AI
  • Extracts skills and job roles from tasks
  • Automatically assigns the best user to tasks
  • Webservice that handles task creation and updates
  • MCP server available from official repository

Use cases of Teamwork.com AI

  • Automating task assignment in Teamwork.com based on user skills and roles
  • Using AI to analyze task descriptions and match them to the most qualified team member
  • Enhancing project management workflows with intelligent task routing

常见问题

1

Is this an official Teamwork.com product?

No, Teamwork.com AI is an **unofficial** extension. The MCP server has been moved to the official Teamwork.com repository for official support.

2

What are the privacy implications of using Teamwork.com AI?

When interacting with LLMs, data you provide may be used to train and improve AI models. This may include sharing data with third-party providers, which could lead to potential privacy and security risks. Always review the privacy policies of AI providers you use.

3

What runtime or dependencies are required?

The project includes a Go badge in the README, but specific runtime requirements are not detailed. The Assigner is a webservice that requires integration with Teamwork.com webhooks.

4

How does the Assigner determine task assignments?

The Assigner uses Agentic AI to extract skills and job roles from task content, then assigns the task to the best user based on that information.

5

Where can I find the MCP server?

The MCP server has moved to the official Teamwork.com repository at https://github.com/teamwork/mcp.

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