Teamwork Projects MCP Server for Vercel AI SDK 17 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Teamwork Projects through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Teamwork Projects, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Teamwork Projects MCP Server
Connect Teamwork to any AI agent and manage your project delivery platform — create and track tasks, manage milestones, log time, post messages, and monitor project progress through natural conversation.
The Vercel AI SDK gives every Teamwork Projects tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 17 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Project Management — List and create projects for organizing work
- Task Management — Create, update, and delete tasks with assignees and due dates
- Milestones — Track project milestones and deadlines
- Time Tracking — Log and review time entries against projects
- Messages — Post announcements and discussions in projects
- Files — List and access project files and attachments
The Teamwork Projects MCP Server exposes 17 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Teamwork Projects to Vercel AI SDK via MCP
Follow these steps to integrate the Teamwork Projects MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 17 tools from Teamwork Projects and passes them to the LLM
Why Use Vercel AI SDK with the Teamwork Projects MCP Server
Vercel AI SDK provides unique advantages when paired with Teamwork Projects through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Teamwork Projects integration everywhere
Built-in streaming UI primitives let you display Teamwork Projects tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Teamwork Projects + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Teamwork Projects MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Teamwork Projects in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Teamwork Projects tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Teamwork Projects capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Teamwork Projects through natural language queries
Teamwork Projects MCP Tools for Vercel AI SDK (17)
These 17 tools become available when you connect Teamwork Projects to Vercel AI SDK via MCP:
create_message
Body should include title and body content. Post a new message in a project
create_milestone
Body should include title and deadline date. Create a new milestone in a project
create_project
Body should include name and optional settings. Create a new project
create_task
Body should include content, tasklist_id, assignee_ids, and due dates. Create a new task
create_time_entry
Body should include description, duration, and date. Log a new time entry
delete_task
Delete a task
get_current_user
Use this to verify connection and identify your user ID. Get the authenticated user profile
get_project
Get details of a specific project
get_task
Get details of a specific task
list_files
List all files in a project
list_messages
List all messages in a project
list_milestones
List all milestones in a project
list_projects
Use project IDs to query tasks, milestones, and other resources within specific projects. List all projects accessible to the user
list_tasklists
Use task list IDs to query specific tasks. List all task lists in a project
list_tasks
List all tasks in a project
list_time_entries
List all time entries in a project
update_task
Update an existing task
Example Prompts for Teamwork Projects in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Teamwork Projects immediately.
"Show me all my projects."
"List all tasks in project 12345."
"Create a milestone 'Phase 1 Complete' with deadline 2025-05-01 in project 12345."
Troubleshooting Teamwork Projects MCP Server with Vercel AI SDK
Common issues when connecting Teamwork Projects to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpTeamwork Projects + Vercel AI SDK FAQ
Common questions about integrating Teamwork Projects MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Teamwork Projects with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Teamwork Projects to Vercel AI SDK
Get your token, paste the configuration, and start using 17 tools in under 2 minutes. No API key management needed.