Teamwork MCP

The Teamwork MCP server is a bridge between AI assistants—such as Claude or Cursor—and the Teamwork project‑management platform. By exposing a rich set of tools that mirror Teamwork’s REST API, it lets developers query and manipulate projects, tasks, people, companies, reports, and time entries directly from an AI conversation. This eliminates the need to write custom API wrappers or handle authentication logic, enabling rapid prototyping of AI‑powered workflows that keep teams in sync with their underlying project data.

At its core, the server offers a clean, typed interface for every common Teamwork operation. Users can list all projects or fetch the details of a single project, create new tasks or subtasks, update status and due dates, and delete obsolete items—all through simple tool calls. The same pattern applies to people management (adding or removing team members from projects), company records, and even granular reporting functions that return CSV or HTML summaries. Each tool is designed to be idempotent and safe, with built‑in error handling that surfaces clear messages back to the AI client.

Developers benefit from a ready‑made integration layer that handles authentication via domain, username, and password. The server automatically manages token renewal and rate‑limit back‑off, so the AI assistant can focus on business logic rather than plumbing. Because every tool is exposed as a declarative action, the MCP can be used with any AI platform that understands the Model Context Protocol, making it a drop‑in solution for enhancing productivity tools, chatbots, or automated reporting systems.

Real‑world use cases include:

• Project Planning: An AI assistant can pull the current project roster, suggest task assignments based on availability, and create new tasks on demand.
• Progress Tracking: By querying task metrics (completed, late) and person utilization reports, the assistant can generate daily stand‑up summaries or risk alerts.
• Resource Management: Teams can add or reassign people to projects, update timezones, and fetch allocation data—all from a single chat interface.
• Reporting Automation: Scheduled reports on task completion or utilization can be delivered to Slack, email, or a dashboard without manual export steps.

The server’s RESTful endpoints and comprehensive tool set make it a versatile component in any AI‑augmented workflow that relies on Teamwork. Its straightforward configuration, combined with robust error handling and logging, ensures reliability in production environments while keeping the developer experience frictionless.