Amazon Bedrock KB MCP Server for Vercel AI SDK 6 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Amazon Bedrock KB through the 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 Bedrock KB, 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 Bedrock KB MCP Server
Connect your Amazon Bedrock account to any AI agent and empower it with managed vector databases, enterprise RAG workflows, and semantic search directly inside AWS.
The Vercel AI SDK gives every Amazon Bedrock KB tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 6 tools through the 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
- Managed RAG — Generate grounded LLM responses using internal document sets in a single explicit call
- Semantic Retrieval — Query vector indexes to retrieve exact top-K text chunks and their origin document URLs
- Data Sources — Inspect and paginate attached storage buckets feeding the knowledge base
- Ingestion Jobs — Track real-time syncing status of chunking pipelines mapping documents across the vector layout
- Knowledge Base Introspection — List available vector stores and exact embedding models assigned directly to your region
The Amazon Bedrock KB MCP Server exposes 6 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 Bedrock KB to Vercel AI SDK via MCP
Follow these steps to integrate the Amazon Bedrock KB 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 6 tools from Amazon Bedrock KB and passes them to the LLM
Why Use Vercel AI SDK with the Amazon Bedrock KB MCP Server
Vercel AI SDK provides unique advantages when paired with Amazon Bedrock KB 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 Bedrock KB integration everywhere
Built-in streaming UI primitives let you display Amazon Bedrock KB 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 Bedrock KB + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Amazon Bedrock KB MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Amazon Bedrock KB in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Amazon Bedrock KB tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Amazon Bedrock KB capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Amazon Bedrock KB through natural language queries
Amazon Bedrock KB MCP Tools for Vercel AI SDK (6)
These 6 tools become available when you connect Amazon Bedrock KB to Vercel AI SDK via MCP:
get_knowledge_base
Get an explicit AWS Bedrock knowledge base
list_data_sources
List Data Sources bound explicitly to an AWS Bedrock KB
list_ingestion_jobs
List AWS Bedrock KB explicit sync operations
list_knowledge_bases
List AWS Bedrock knowledge bases
retrieve
Query a vector index securely via AWS Bedrock
retrieve_and_generate
Generate explicitly grounded LLM responses using Bedrock KB
Example Prompts for Amazon Bedrock KB in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Amazon Bedrock KB immediately.
"Which knowledge bases and embedding models do I have setup?"
"Run a retrieval query for 'onboarding process checklist' on my KB and show me the top 3 snippets."
"Check the status of the S3 ingestion job for my Documentation bucket."
Troubleshooting Amazon Bedrock KB MCP Server with Vercel AI SDK
Common issues when connecting Amazon Bedrock KB to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpAmazon Bedrock KB + Vercel AI SDK FAQ
Common questions about integrating Amazon Bedrock KB 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 Bedrock KB 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 Bedrock KB to Vercel AI SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.