Amazon Redshift MCP Server for Vercel AI SDK 7 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Amazon Redshift 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 Amazon Redshift, 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 Amazon Redshift MCP Server
Connect your Amazon Redshift data warehouse securely to your AI agent utilizing the AWS Redshift Data API. This integration empowers your AI interface to natively run aggregations, explore massive schemas, and retrieve historical executing query logs asynchronously without requiring persistent DB connection pools, JDBC drivers, or complex networking configurations.
The Vercel AI SDK gives every Amazon Redshift 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
- Execute Asynchronous SQL — Direct the AI to execute standard SQL commands (
execute_sql), including complex SELECT aggregations, table creation (DDL), or data mutation (DML). Since it uses the Data API, long-running queries will process in the background. - Poll & Retrieve Results — Ask the agent to proactively monitor the execution lifecycle (
statement_status) of dispatched query IDs and retrieve the dataset rows (get_results) securely into your terminal upon completion. - Schema & Table Discovery — Understand the database structure dynamically by generating lists of available schemas (
list_schemas) or looking up column metadata metrics for specific tables (describe_table). - Statement Histories — Perform audits assessing previously submitted query structures and track analytical workloads running on your configured cluster (
list_statements).
The Amazon Redshift 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.
How to Connect Amazon Redshift to Vercel AI SDK via MCP
Follow these steps to integrate the Amazon Redshift 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 7 tools from Amazon Redshift and passes them to the LLM
Why Use Vercel AI SDK with the Amazon Redshift MCP Server
Vercel AI SDK provides unique advantages when paired with Amazon Redshift 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 Amazon Redshift integration everywhere
Built-in streaming UI primitives let you display Amazon Redshift 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
Amazon Redshift + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Amazon Redshift MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Amazon Redshift in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Amazon Redshift tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Amazon Redshift capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Amazon Redshift through natural language queries
Amazon Redshift MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect Amazon Redshift to Vercel AI SDK via MCP:
describe_table
Retrieves column metadata for a table
execute_sql
This is an asynchronous operation that returns a statement ID. Executes a SQL statement using the Redshift Data API
get_results
Retrieves the results of a completed SQL statement
list_schemas
Lists all database schemas in Redshift
list_statements
Lists recent SQL statements executed in the cluster
list_tables
Lists all tables in a specific schema
statement_status
Checks the execution status of a SQL statement
Example Prompts for Amazon Redshift in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Amazon Redshift immediately.
"List all active tables present inside the 'reporting_schema' schema."
"Describe the column parameters for 'user_cohorts' in the reporting schema."
"Run a query to fetch the sum of sales amounts where region is 'APAC' from the 'quarterly_revenue' table."
Troubleshooting Amazon Redshift MCP Server with Vercel AI SDK
Common issues when connecting Amazon Redshift to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpAmazon Redshift + Vercel AI SDK FAQ
Common questions about integrating Amazon Redshift 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 Amazon Redshift 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 Amazon Redshift to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.