Teamwork AI MCP Server

The Teamwork.com AI MCP server is an unofficial bridge that brings the full power of Teamwork’s project‑management platform into the conversational world of large language models. By exposing a rich set of tools over the Model Context Protocol, it lets AI assistants create projects, task lists, tasks, and even perform intelligent assignment of work to team members—all without leaving the chat interface. For developers building agentic workflows, this means a single integration point that turns natural‑language requests into concrete actions inside Teamwork, saving time and reducing context switching.

At its core, the server translates high‑level prompts into Teamwork API calls. When an AI client asks to “create a project with the steps to build a new house,” the MCP server constructs a project named New House, automatically generates a task list, and populates it with detailed tasks derived from the conversation. The server also supports advanced scenarios such as skill‑based task assignment: it queries existing projects, members, and their declared skills, then matches tasks to the most suitable users. If no match is found, it gracefully leaves tasks unassigned, allowing human oversight.

Key capabilities include:

• Task and project orchestration – Create, update, and delete projects or tasks directly from chat.
• Skill‑aware assignment – Leverage Teamwork’s skill taxonomy to auto‑assign work based on user expertise.
• Webhook integration – The companion Assigner service listens to Teamwork webhooks, turning new or updated tasks into AI‑driven assignment decisions in real time.
• Prompt customization – Developers can expose custom prompts and sampling controls, tailoring the assistant’s behavior to their workflow.

Real‑world use cases are plentiful. A product manager can ask the assistant to lay out a release plan; the MCP server will generate the necessary tasks and distribute them among engineers. A project lead can request a re‑allocation of resources when deadlines shift, and the server will automatically reassign tasks to the most qualified team members. In support teams, new tickets can be turned into actionable tasks and assigned to the right specialist instantly.

Integration is seamless: once a developer registers the MCP server with their AI platform, any supported client can invoke its tools through standard MCP calls. The Assigner service adds an extra layer of automation by reacting to live Teamwork events, making the entire system reactive and agentic. This combination of conversational control, intelligent assignment, and real‑time integration gives developers a powerful, low‑friction way to embed Teamwork’s capabilities into AI‑driven productivity workflows.