Plecto MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 11 tools to Create Data Registration, Get Dashboard, Get Employee, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Plecto 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 Plecto app connector for Vercel AI SDK is a standout in the Productivity category — giving your AI agent 11 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 Plecto, 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 Plecto MCP Server
Connect your Plecto account to any AI agent and simplify your KPI tracking, performance management, and dashboard orchestration through natural conversation.
The Vercel AI SDK gives every Plecto tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 11 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
- Data Registrations — List all data entries for any data source, retrieve detailed metadata, and monitor real-time values
- Direct Execution — Create new data registrations programmatically directly from your agent to feed your dashboards
- KPI Dashboards — Query all configured KPI dashboards and retrieve detailed metadata to monitor performance
- Team Coordination — List organizational teams and employees to manage access and resource allocation
- Data Sources — Query all configured data sources to choose the right context for each interaction
The Plecto MCP Server exposes 11 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 11 Plecto tools available for Vercel AI SDK
When Vercel AI SDK connects to Plecto through Vinkius, your AI agent gets direct access to every tool listed below — spanning kpi-tracking, performance-management, real-time-data, 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.
Add a new data entry
Get details for a specific dashboard
Get details for a specific employee
Get details for a specific data registration
List account employees
List Plecto registrations
List Plecto data sources
List all KPI formulas
List Plecto dashboards
List teams
List all widgets on a dashboard
Connect Plecto to Vercel AI SDK via MCP
Follow these steps to wire Plecto 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 Plecto MCP Server
Vercel AI SDK provides unique advantages when paired with Plecto 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 Plecto integration everywhere
Built-in streaming UI primitives let you display Plecto 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
Plecto + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Plecto MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Plecto in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Plecto tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Plecto capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Plecto through natural language queries
Example Prompts for Plecto in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Plecto immediately.
"List all my KPI dashboards in Plecto."
"Show me the sales leaderboard for the current month with all team member performance metrics."
"Register a new data point for Sarah Chen with $45,000 in closed deals today on the Revenue data source."
Troubleshooting Plecto MCP Server with Vercel AI SDK
Common issues when connecting Plecto to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpPlecto + Vercel AI SDK FAQ
Common questions about integrating Plecto 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.