Zenkit MCP Server for Vercel AI SDK 8 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Zenkit 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 Zenkit, 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 Zenkit MCP Server
Connect your Zenkit account to any AI agent to streamline your productivity and project management. This MCP server enables your agent to interact with workspaces, lists (collections), and data entries directly from natural language.
The Vercel AI SDK gives every Zenkit tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 8 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
- Workspace Oversight — List all workspaces and retrieve their constituent lists and metadata
- List Management — Query detailed configurations and field elements for any Zenkit list
- Data Operations — List, retrieve, create, and update entries (items) within your collections
- Field Discovery — Inspect list elements to understand the data structure and field types
- Content Cleanup — Delete entries and maintain your lists directly via natural language commands
The Zenkit MCP Server exposes 8 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 Zenkit to Vercel AI SDK via MCP
Follow these steps to integrate the Zenkit 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 8 tools from Zenkit and passes them to the LLM
Why Use Vercel AI SDK with the Zenkit MCP Server
Vercel AI SDK provides unique advantages when paired with Zenkit 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 Zenkit integration everywhere
Built-in streaming UI primitives let you display Zenkit 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
Zenkit + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Zenkit MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Zenkit in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Zenkit tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Zenkit capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Zenkit through natural language queries
Zenkit MCP Tools for Vercel AI SDK (8)
These 8 tools become available when you connect Zenkit to Vercel AI SDK via MCP:
create_entry
Requires a JSON object with field values. Create a new entry in a list
delete_entry
Delete an entry from a list
get_list_details
Get details for a specific list
get_workspace_details
Get details for a specific workspace
list_elements
List all elements (fields) defined in a list
list_entries
List all entries (items) in a list
list_workspaces
List all workspaces and their lists
update_entry
Update an existing entry
Example Prompts for Zenkit in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Zenkit immediately.
"List all my Zenkit workspaces and their collections."
"Show me all entries in the list with ID '98765'."
"Create a new entry in list '98765' with name 'Finish API documentation'."
Troubleshooting Zenkit MCP Server with Vercel AI SDK
Common issues when connecting Zenkit to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpZenkit + Vercel AI SDK FAQ
Common questions about integrating Zenkit 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 Zenkit 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 Zenkit to Vercel AI SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.