How to Use the Veraset MCP in Vercel AI SDK

Q: Does the MCP Server handle dataset metadata for Vercel AI SDK?

Absolutely. You use getdatasetmetadata to retrieve technical details about any Veraset mobility dataset, giving you context beyond just the column names.

Q: If I want to download raw data from Veraset with Vercel AI SDK, what do I need?

You'll use generatedownloadlink. This tool creates a temporary, pre-signed URL for an S3 file. You can then pass that link directly to your frontend.

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Connect Veraset MCP to Vercel AI SDK

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

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Real-time SQL Querying

Run complex geospatial queries and see the output stream right into the user interface. Instead of waiting for a loading spinner, your client streams results as they appear using `execute_sql_query`. You can track progress mid-run by checking `get_query_status`, letting users know exactly when their query against Veraset is finished.

Data Structure Inspection

Need to know what columns are available before writing SQL? Your agent client uses `get_dataset_schema` to pull definitions and data types for any specific dataset. It also grabs a quick look at the data with `get_dataset_sample`, so you can validate your query logic immediately on the Veraset side.

Managing Data Access

The MCP Server lets your agent identify all accessible data sources by calling `list_mobility_datasets`. It's also smart enough to list S3 drop folders using `list_s3_delivery_folders`. Once the query is done, you can get the final results or a download link via `get_query_results` or `generate_download_link`, streaming everything out.

Setup guide

Set up Veraset 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 Veraset 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 Veraset 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 Veraset. 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 Veraset MCP in Vercel AI SDK

The MCP Server supports pagination for result retrieval. When you call `get_query_results`, your client can request chunks of data, preventing massive payload failures and keeping the stream running smoothly.

You'll find mobility-focused datasets. You can see exactly what’s available by calling `list_mobility_datasets` first, which tells you all the data pools ready for analysis.

Yep. If a geospatial SQL query gets stuck or runs too long, your agent can immediately abort it by invoking `cancel_running_query`. That keeps the client responsive.

Absolutely. You use `get_dataset_metadata` to retrieve technical details about any Veraset mobility dataset, giving you context beyond just the column names.

You'll use `generate_download_link`. This tool creates a temporary, pre-signed URL for an S3 file. You can then pass that link directly to your frontend.

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