Google Roads MCP Server for Vercel AI SDK 4 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Google Roads 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 Google Roads, 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 Google Roads MCP Server
Connect your Google Roads API to any AI agent and take full control of GPS map matching, road segment identification, and speed limit data retrieval through natural conversation.
The Vercel AI SDK gives every Google Roads tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 4 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
- Snap to Roads — Match GPS coordinate paths to the most likely roads travelled with interpolated points for smooth road geometry
- Nearest Roads — Find the nearest road segment for up to 100 individual GPS coordinates independently
- Speed Limits — Get posted speed limit data for specific road segments using place IDs from road matching
- Snapped Speed Limits — Snap GPS coordinates to roads AND get speed limits in a single combined request
- Place ID Mapping — Obtain Google place IDs for road segments that can be used with other Google Maps APIs
- Fleet Tracking — Clean noisy GPS traces from fleet vehicles for accurate route visualization
- GPS Correction — Convert raw GPS points into accurate road-level positions for mapping applications
The Google Roads MCP Server exposes 4 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 Google Roads to Vercel AI SDK via MCP
Follow these steps to integrate the Google Roads 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 4 tools from Google Roads and passes them to the LLM
Why Use Vercel AI SDK with the Google Roads MCP Server
Vercel AI SDK provides unique advantages when paired with Google Roads 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 Google Roads integration everywhere
Built-in streaming UI primitives let you display Google Roads 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
Google Roads + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Google Roads MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Google Roads in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Google Roads tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Google Roads capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Google Roads through natural language queries
Google Roads MCP Tools for Vercel AI SDK (4)
These 4 tools become available when you connect Google Roads to Vercel AI SDK via MCP:
get_nearest_roads
Returns the snapped coordinate, the original coordinate, and the place ID for each nearest road segment. Unlike snapToRoads which assumes coordinates form a continuous path, nearestRoads treats each point independently. Essential for reverse geocoding, finding which road a vehicle is on, identifying road segments for individual location points, and mapping scattered GPS points to roads. Each point is matched to the nearest road segment within a reasonable distance. Place IDs can be used with the speed limits endpoint. AI agents should reference this when users ask "what road is at these coordinates", "find the nearest road for each GPS point", or need to map individual location points to road segments without assuming a path. Get the nearest road segments for up to 100 individual GPS coordinates
get_snapped_speed_limits
Snaps GPS coordinates to the nearest road segments and returns both the snapped coordinates with place IDs AND the speed limits for each road segment. This is more efficient than making separate calls to snapToRoads and then speedLimits. Returns snapped points with place IDs, original coordinates, and speed limit data in km/h for each road segment. Essential for applications that need both map-matched road geometry and speed limit data, such as fleet management, driver safety monitoring, route planning with speed awareness, and GPS track analysis. AI agents should reference this when users ask "snap these GPS points to roads and show speed limits", "get both snapped coordinates and speed limits for this route", or need combined road matching and speed limit data in one call. Snap GPS coordinates to roads and get speed limits in a single request
get_speed_limits
Returns speed limit values in km/h along with the place IDs and corresponding road segment information. Place IDs are obtained from the snapToRoads or nearestRoads responses. Essential for speed compliance monitoring, fleet safety management, driver behavior analysis, and road safety applications. Speed limits reflect posted legal limits and may vary by road type, urban/rural designation, and local regulations. AI agents should use this when users ask "what is the speed limit on this road segment", "get speed limits for these place IDs", or need speed limit data for specific road segments identified through map matching. Get speed limit data for specific road segments using place IDs
snap_to_roads
Returns snapped coordinates with place IDs, original coordinates, and interpolated points along the road. Essential for map matching, GPS track correction, route reconstruction, fleet tracking visualization, and converting raw GPS traces into clean road geometries. The path parameter accepts up to 100 coordinate pairs in "lat,lng|lat,lng" format. Set interpolate=true to return additional points between input coordinates for smoother road geometry. Place IDs returned can be used with the speed limits endpoint to get speed limit data for each road segment. AI agents should use this when users ask "snap this GPS track to roads", "match these coordinates to the actual roads travelled", or need to clean up noisy GPS data for mapping and visualization. Snap GPS coordinates to the most likely roads travelled using Google Roads API
Example Prompts for Google Roads in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Google Roads immediately.
"Snap these GPS coordinates to roads: 40.7128,-74.0060|40.7135,-74.0055|40.7142,-74.0048"
"Get speed limits for these place IDs: ChIJd8BlQ2BZwokRAFUEcm_qrcA|ChIJd8BlQ2BZwokRAFUEcm_qrcB"
"Find the nearest road to these coordinates: 34.0522,-118.2437 and 34.0530,-118.2445"
Troubleshooting Google Roads MCP Server with Vercel AI SDK
Common issues when connecting Google Roads to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpGoogle Roads + Vercel AI SDK FAQ
Common questions about integrating Google Roads 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 Google Roads 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 Google Roads to Vercel AI SDK
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.