Deepgram MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 6 tools to Convert Text To Speech, Get Project Usage, List Api Keys, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Deepgram 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 Deepgram app connector for Vercel AI SDK is a standout in the Ai Frontier category — giving your AI agent 6 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 Deepgram, 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 Deepgram MCP Server
Connect your Deepgram account to any AI agent and take full control of your speech-to-text (STT) and text-to-speech (TTS) workflows through natural conversation.
The Vercel AI SDK gives every Deepgram tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 6 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
- Transcription Orchestration — Convert speech from public audio or video URLs into high-fidelity text programmatically using the latest Nova-3 models with smart formatting and diarization
- Neural Speech Synthesis — Programmatically generate natural-sounding audio from text input using the high-speed Aura engine to coordinate voice-enabled interfaces
- Model Discovery — Access complete directories of high-performance STT and TTS models supported by Deepgram to ensure the perfect accuracy and latency for your content
- Project & Usage Monitoring — Programmatically track your API utilization, minute consumption, and request counts across multiple projects for instant operational reporting
- Credential Lifecycle — Retrieve identifiers for active API keys associated with your projects directly through your agent to maintain high-fidelity security oversight
The Deepgram 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.
All 6 Deepgram tools available for Vercel AI SDK
When Vercel AI SDK connects to Deepgram through Vinkius, your AI agent gets direct access to every tool listed below — spanning speech-to-text, text-to-speech, transcription, 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.
Generate audio from text (TTS)
Check API usage and limits
List active API keys
List high-performance AI models
List your Deepgram projects
Transcribe an audio file via URL
Connect Deepgram to Vercel AI SDK via MCP
Follow these steps to wire Deepgram 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 Deepgram MCP Server
Vercel AI SDK provides unique advantages when paired with Deepgram 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 Deepgram integration everywhere
Built-in streaming UI primitives let you display Deepgram 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
Deepgram + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Deepgram MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Deepgram in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Deepgram tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Deepgram capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Deepgram through natural language queries
Example Prompts for Deepgram in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Deepgram immediately.
"Transcribe the audio from this URL: 'https://static.deepgram.com/examples/interview_segments_nuwav.wav'."
"Convert this text to speech: 'Deepgram is the fastest way to add voice to your AI'."
"List all active API keys for project 'proj_123'."
Troubleshooting Deepgram MCP Server with Vercel AI SDK
Common issues when connecting Deepgram to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpDeepgram + Vercel AI SDK FAQ
Common questions about integrating Deepgram 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.