How to Use the BallotReady MCP in Vercel AI SDK

Q: Can I stream BallotReady results to a Next.js app with Vercel AI SDK?

Yes, the integration is built specifically for this. Call listcandidates on the server and pipe the response directly to your client components. The user reads the names as they generate.

Connect the BallotReady MCP Server to Vercel AI SDK and stream live election data directly into your frontend interfaces.

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Connect BallotReady MCP to Vercel AI SDK

Create your Vinkius account to connect BallotReady 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 BallotReady with Vercel AI SDK

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Stream Local Elections via MCP Server

Connecting this MCP Server to your frontend eliminates the loading spinner when fetching voting data. Your React components render civic details as they stream in from the API. Call `get_elections_by_address` and watch the upcoming local races appear instantly in your application. Users see the exact dates and deadlines materializing on screen without refreshing the page.

Render Candidate Profiles Live

The `get_candidate` tool pulls massive amounts of biographical data directly into your edge functions. The AI client processes the raw JSON and generates readable bios on the fly. You pass the candidate ID, and the text streams straight into your Next.js layout. Voters read about their local politicians' backgrounds while the `list_positions` tool continues fetching the remaining down-ballot races in parallel.

Map Districts to Addresses

The `get_districts_by_address` tool matches physical locations to their exact political boundaries instantly. Figuring out someone's exact voting district is notoriously difficult due to weird boundary lines. Your Svelte app captures a user's street address and hands it to the SDK. Within milliseconds, `get_officeholders` populates the UI with the exact people currently representing that specific home.

Setup guide

Set up BallotReady 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 BallotReady 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 BallotReady transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by BallotReady. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about BallotReady MCP in Vercel AI SDK

Install both the core AI package and the MCP Server integration via npm. Initialize the connection using createMCPClient with your HTTP transport URL. Pass the resulting tools to your streamText function.

Yes, the integration is built specifically for this. Call `list_candidates` on the server and pipe the response directly to your client components. The user reads the names as they generate.

It handles edge environments perfectly. You just need to ensure you call the close method on the client after the stream finishes to prevent hanging connections.

You skip writing the glue code. The AI understands the schema for `get_ballot_measures` out of the box and formats the output for your users automatically.

Vinkius processes all physical street addresses inside ephemeral, isolated V8 sandboxes. The container spins up for the exact duration of the `list_districts` call and self-destructs immediately after. Zero data persists on our infrastructure.

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