How to Use the Federal Register MCP in Vercel AI SDK

Q: How do I stream Federal Register documents using the Vercel AI SDK?

You initialize the client using createMCPClient with your HTTP endpoint. Then, pass the tools from mcpClient.tools() directly to streamText to let your model call getdocument and stream the output to your frontend.

Q: How does the Vercel AI SDK handle multiple Federal Register document requests?

The SDK calls getmultipledocuments when the user requests a batch of regulations. It streams the combined text payload back to the UI, so your users see the results compile in real-time.

Q: Is my search query data private when using the Vercel AI SDK to search the Federal Register?

Yes, all search queries sent to searchdocuments run through an MCP sandbox that never logs your inputs. Your regulatory research parameters remain strictly between your frontend and the official federal API.

Stream real-time government regulatory filings directly into your Next.js frontend with the Vercel AI SDK.

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Connect Federal Register MCP to Vercel AI SDK

Create your Vinkius account to connect Federal Register 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 Federal Register with Vercel AI SDK

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Stream Live Federal Inspection Documents

Don't make users wait for heavy Federal Register updates to load in your React app. With this MCP Server, your Vercel AI SDK app streams raw text from `get_current_public_inspection` directly to the browser as it lands. Your Next.js UI updates instantly when new filings appear on the public inspection list. By passing `get_public_inspection_document` to your Vercel AI SDK stream, you bypass standard API latency and display critical legal updates line-by-line.

Build Interactive Vercel AI SDK Search Tools

Build a real-time search interface for government filings without writing a custom backend. The Vercel AI SDK hooks directly into `search_documents` to pull matching Federal Register regulations on the fly. When a user asks about a specific policy, the Vercel AI SDK resolves the query using `get_document` and renders the official text immediately. You get clean markdown streaming straight into your React components without complex state management.

Map Agency Hierarchies on the Edge

Run lightweight compliance lookups globally on Vercel Edge Functions. This setup lets your Vercel AI SDK client call `list_agencies` to map out the entire structure of the executive branch without cold starts. Once the user selects an agency, your Vercel AI SDK system uses `get_agency` to fetch contact details and active documents. It keeps your edge bundle small because the heavy lifting happens on the hosted MCP Server.

Setup guide

Set up Federal Register 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 Federal Register 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 Federal Register 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 Federal Register. 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 Federal Register MCP in Vercel AI SDK

You initialize the client using `createMCPClient` with your HTTP endpoint. Then, pass the tools from `mcpClient.tools()` directly to `streamText` to let your model call `get_document` and stream the output to your frontend.

Yes, the HTTP transport is fully compatible with Edge runtimes. You can call `search_documents` to find federal filings from any global edge location without worrying about Node.js dependencies.

The SDK calls `get_multiple_documents` when the user requests a batch of regulations. It streams the combined text payload back to the UI, so your users see the results compile in real-time.

No, the server does that work for you. When your code invokes `get_public_inspection_document`, it returns clean, structured text that the Vercel AI SDK can instantly read and format for your UI.

Yes, all search queries sent to `search_documents` run through an MCP sandbox that never logs your inputs. Your regulatory research parameters remain strictly between your frontend and the official federal API.

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