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Vinkius

Jestor MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Jestor through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Vinkius supports streamable HTTP and SSE.

typescript
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 Jestor, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
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* 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 Jestor MCP Server

Empower your AI agents with Jestor's low-code internal tools platform. This MCP server allows you to list objects (tables), retrieve and list records, manage users, and monitor workflows and dashboards directly through the Jestor API. Ideal for automating internal operations and database management.

The Vercel AI SDK gives every Jestor tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

The Jestor MCP Server exposes 10 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 Jestor to Vercel AI SDK via MCP

Follow these steps to integrate the Jestor MCP Server with Vercel AI SDK.

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the script

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

The SDK discovers 10 tools from Jestor and passes them to the LLM

Why Use Vercel AI SDK with the Jestor MCP Server

Vercel AI SDK provides unique advantages when paired with Jestor through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Jestor integration everywhere

03

Built-in streaming UI primitives let you display Jestor tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Jestor + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the Jestor MCP Server delivers measurable value.

01

AI-powered web apps: build dashboards that query Jestor in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate Jestor tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed Jestor capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with Jestor through natural language queries

Jestor MCP Tools for Vercel AI SDK (10)

These 10 tools become available when you connect Jestor to Vercel AI SDK via MCP:

01

get_me

Use this to verify connection status and current permissions. Gets current authenticated user info

02

get_object

Useful for understanding field types and relationships within a specific table. Retrieves details/schema for a specific object

03

get_record

Essential for deep-diving into a specific entry in the database. Retrieves details for a specific record

04

list_apps

Useful for discovering high-level toolsets available to the user. Lists all installed internal apps

05

list_dashboards

Use this to identify where aggregated data visualizations are located. Lists all configured dashboards

06

list_objects

Returns object names and labels. Use this to discover available datasets before querying specific records. Lists all objects (tables) in your Jestor account

07

list_records

This is the primary tool for browsing data within a table (e.g., listing all "Tasks" or "Clients"). Lists records for a specific object

08

list_users

Returns names, emails, and IDs. Useful for identifying record owners or system administrators. Lists all users in the organization

09

list_webhooks

Use this to audit third-party integrations. Lists all configured webhooks

10

list_workflows

Useful for auditing system logic and event-driven actions. Lists all automated workflows

Example Prompts for Jestor in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Jestor immediately.

01

"List all objects in my Jestor account."

02

"Show me the records for the 'Invoices' object."

03

"Check the status of my workflows."

Troubleshooting Jestor MCP Server with Vercel AI SDK

Common issues when connecting Jestor to Vercel AI SDK through the Vinkius, and how to resolve them.

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Jestor + Vercel AI SDK FAQ

Common questions about integrating Jestor MCP Server with Vercel AI SDK.

01

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
02

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
03

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

Connect Jestor to Vercel AI SDK

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.