Tinybird Data Platform MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Tinybird Data Platform 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 Tinybird Data Platform, 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 Tinybird Data Platform MCP Server
Connect your AI agent to Tinybird, the real-time data platform for developers. This integration allows you to oversee your analytical infrastructure, manage ingestion storage (Data Sources), and interact with transformation logic (Pipes) through natural conversation.
The Vercel AI SDK gives every Tinybird Data Platform 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.
What you can do
- Infrastructure Oversight — List and inspect all your Data Sources and Pipes in real-time
- Transformation Analysis — Retrieve SQL logic and nodes for any Pipe to understand how data is being processed
- Live Querying — Execute published Pipes or run arbitrary SQL queries (ClickHouse dialect) to explore your data directly via the agent
- Operational Metrics — Check ingestion stats, row counts, and storage sizes for your analytical units
- Access Control — List and audit authentication tokens and workspace configurations
The Tinybird Data Platform 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 Tinybird Data Platform to Vercel AI SDK via MCP
Follow these steps to integrate the Tinybird Data Platform 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 10 tools from Tinybird Data Platform and passes them to the LLM
Why Use Vercel AI SDK with the Tinybird Data Platform MCP Server
Vercel AI SDK provides unique advantages when paired with Tinybird Data Platform 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 Tinybird Data Platform integration everywhere
Built-in streaming UI primitives let you display Tinybird Data Platform 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
Tinybird Data Platform + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Tinybird Data Platform MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Tinybird Data Platform in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Tinybird Data Platform tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Tinybird Data Platform capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Tinybird Data Platform through natural language queries
Tinybird Data Platform MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Tinybird Data Platform to Vercel AI SDK via MCP:
execute_sql_query
Execute an arbitrary SQL query against the Tinybird workspace
get_datasource_details
Get comprehensive information for a specific Data Source
get_datasource_stats
Retrieve ingestion and usage statistics for a Data Source
get_pipe_details
Get detailed information for a specific Pipe
list_auth_tokens
Retrieve a list of all authentication tokens in the workspace
list_datasources
Retrieve a list of all Data Sources in the current workspace
list_pipe_nodes
List all SQL nodes within a specific Pipe
list_pipes
Retrieve a list of all Pipes in the current workspace
list_workspaces
Retrieve a list of available workspaces
query_pipe_data
Execute a Pipe and retrieve the results as JSON
Example Prompts for Tinybird Data Platform in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Tinybird Data Platform immediately.
"List all data sources in my Tinybird workspace."
"Run the pipe 'monthly_revenue_summary' with limit 5."
Troubleshooting Tinybird Data Platform MCP Server with Vercel AI SDK
Common issues when connecting Tinybird Data Platform to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpTinybird Data Platform + Vercel AI SDK FAQ
Common questions about integrating Tinybird Data Platform 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 Tinybird Data Platform 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 Tinybird Data Platform to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.