Veraset MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Veraset through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
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 Veraset, 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 Veraset MCP Server
Bind the massive scale of Veraset geolocation data directly to your preferred AI conversational agent. Eradicate context switching when analyzing billions of Points of Interest (POI) and mobile signal attributes.
The Vercel AI SDK gives every Veraset tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 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
- Live SQL Querying — Prompt your LLM agent to construct, dispatch, and execute ANSI SQL directly aimed at Veraset databases to compute geolocation aggregates.
- Rapid Execution Management — Check on long-running geolocation jobs, pull back the output tables seamlessly, or ruthlessly cancel intensive queries straight from your text box.
- Dataset Profiling — Scan all your available Veraset packages, request quick dataset schemas, or instantly preview data samples to ensure accuracy before executing queries.
- Delivery Bucket Access — Query the secure S3 delivery prefixes attached to your organization for bulk downloads and dynamically generate pre-signed file keys in seconds.
The Veraset MCP Server exposes 10 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.
How to Connect Veraset to Vercel AI SDK via MCP
Follow these steps to integrate the Veraset MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from Veraset and passes them to the LLM
Why Use Vercel AI SDK with the Veraset MCP Server
Vercel AI SDK provides unique advantages when paired with Veraset 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 Veraset integration everywhere
Built-in streaming UI primitives let you display Veraset 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
Veraset + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Veraset MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Veraset in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Veraset tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Veraset capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Veraset through natural language queries
Veraset MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Veraset to Vercel AI SDK via MCP:
cancel_running_query
Immediately aborts a currently executing SQL task
execute_sql_query
Provide a dataset ID and ANSI SQL. Returns a query ID. Starts a new SQL query task against a Veraset dataset
generate_download_link
Generates a temporary pre-signed URL for an S3 file download
get_dataset_metadata
Retrieves technical metadata for a specific mobility dataset
get_dataset_sample
Retrieves a quick sample of the first few rows of a dataset
get_dataset_schema
Retrieves the column definitions and data types for a dataset
get_query_results
Supports pagination. Retrieves the result rows from a completed SQL query
get_query_status
Checks the progress of a running SQL query
list_mobility_datasets
Identify accessible mobility datasets in Veraset
list_s3_delivery_folders
Lists S3 prefixes where scheduled data drops are delivered
Example Prompts for Veraset in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Veraset immediately.
"List all our provisioned delivery folder buckets for S3 mobility packets."
"Get a basic preview 10-row sample from the dataset 'movement_global'."
"Execute an aggregation query on 'dataset-v5' grouping total foot traffic by 'store_id' and get the current execution status."
Troubleshooting Veraset MCP Server with Vercel AI SDK
Common issues when connecting Veraset to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpVeraset + Vercel AI SDK FAQ
Common questions about integrating Veraset 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.Connect Veraset with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Veraset to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.