Dovetail MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 7 tools to Create Insight, Create Note, Get Project Details, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Dovetail through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
Ask AI about this App Connector for Vercel AI SDK
The Dovetail app connector for Vercel AI SDK is a standout in the Productivity category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Dovetail, 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 Dovetail MCP Server
Connect your Dovetail account to any AI agent and take full control of your user research and insight management workflows through natural conversation.
The Vercel AI SDK gives every Dovetail tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 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 Orchestration — List and manage research projects programmatically and retrieve detailed metadata about goals and participants
- Note Architecture — Create and organize research notes (interviews, usability tests, raw data) with specific content types (HTML, Markdown) directly from your agent
- Insight Management — Programmatically publish research findings and summaries to maintain a high-fidelity record of your team's discoveries
- Deep Search — Find relevant research data across projects using powerful query filters for titles and content
- Workspace Visibility — Retrieve complete directories of workspace members to coordinate collaboration and manage team access
The Dovetail MCP Server exposes 7 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.
All 7 Dovetail tools available for Vercel AI SDK
When Vercel AI SDK connects to Dovetail through Vinkius, your AI agent gets direct access to every tool listed below — spanning dovetail, user-research, insights-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new research insight
Create a new research note
Get details for a research project
List research insights
List research notes
List all research projects
List workspace members
Connect Dovetail to Vercel AI SDK via MCP
Follow these steps to wire Dovetail into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
npm install @ai-sdk/mcp ai @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the script
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Vercel AI SDK with the Dovetail MCP Server
Vercel AI SDK provides unique advantages when paired with Dovetail 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 Dovetail integration everywhere
Built-in streaming UI primitives let you display Dovetail 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
Dovetail + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Dovetail MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Dovetail in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Dovetail tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Dovetail capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Dovetail through natural language queries
Example Prompts for Dovetail in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Dovetail immediately.
"List all my research projects in Dovetail."
"Create a new research note 'User A Interview' in project 'proj_123'."
"Show me all published insights containing the word 'mobile'."
Troubleshooting Dovetail MCP Server with Vercel AI SDK
Common issues when connecting Dovetail to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpDovetail + Vercel AI SDK FAQ
Common questions about integrating Dovetail 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.