How to Use the Fireflies.ai MCP in Vercel AI SDK

Stream meeting data directly into your Vercel AI SDK frontends. Access your transcripts and analytics in real-time.

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Connect Fireflies.ai MCP to Vercel AI SDK

Create your Vinkius account to connect Fireflies.ai to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Fireflies.ai with Vercel AI SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Live meeting data in your UI

Pipe transcriptions into your React components without waiting for backend polling. Use `get_transcript` to push raw text into your state management layer the moment it hits your server. Your users watch the conversation flow as it happens. This MCP Server keeps your UI in sync with the live meeting state through streamText calls.

Query meeting history via SDK tools

Feed your language models the context they need by calling `list_transcripts` directly from your server-side functions. It pulls the metadata you need to populate search indexes or dashboard lists. Everything happens within the Vercel edge runtime. You get the specific transcript data you request without the overhead of manual API integration logic.

Manage threads for smarter AI responses

Build chat interfaces that remember previous discussions using `list_ask_fred_threads`. You retrieve existing conversation history and inject it into your prompt chain immediately. Use `create_ask_fred_thread` to start new analysis sessions based on current user input. Your AI client handles the heavy lifting while you focus on the UI.

Setup guide

Set up Fireflies.ai MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Fireflies.ai tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Fireflies.ai transactions",
});

console.log(text);
await mcpClient.close();

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Common questions about Fireflies.ai MCP in Vercel AI SDK

You instantiate the client and pass the tools to your model. The SDK handles the transport layer, letting you call the server tools as standard functions.

Yes. The server returns transcript segments which you can stream directly into your UI. It avoids memory bloat by processing only what you request.

It does. Because the server tools are compatible with the SDK, you can pipe the tool output into your streaming text response.

Use environment variables on your Vercel project. Never expose your API keys in the client-side code.

Your transcripts remain on the provider's servers. You only request specific text segments through the MCP interface, and the data is encrypted during transit.

Use it with your favorite AI tools

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