Vinkius

Google Roads MCP. Map raw GPS data to accurate, actionable street geometry.

Google Roads provides precise mapping tools to match raw GPS data to actual road networks anywhere in the world. Use this MCP to snap scattered coordinates to the nearest roads, reconstruct accurate travel paths, and retrieve official speed limit data for specific segments. It’s essential infrastructure for anyone building location-aware applications or analyzing vehicle telemetry.

Google Roads MCP is compatible with Claude Claude
Google Roads MCP is compatible with ChatGPT ChatGPT
Google Roads MCP is compatible with Cursor Cursor
Google Roads MCP is compatible with Gemini Gemini
Google Roads MCP is compatible with Windsurf Windsurf
Google Roads MCP is compatible with VS Code VS Code
Google Roads MCP is compatible with JetBrains JetBrains
Google Roads MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Match GPS tracks to roads

Transforms a series of raw coordinates into a clean, continuous path that follows the actual road geometry.

Find nearest roadside segment

Identifies the specific, closest road segment for individual GPS points, treating each point independently rather than as part of a path.

Retrieve speed limit data

Gets posted legal speed limits (in km/h) by referencing the unique identifiers of matched road segments.

Combine snapping and speed checks

Performs both map matching and speed limit retrieval in a single, efficient request to save API calls.

Correct noisy GPS data

Cleans up messy telemetry from vehicles by converting scattered points into accurate road-level positions.

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AI Agent
Google Roads

What AI agents can do with Google Roads: 4 Tools for Geospatial Analysis

These tools allow you to snap raw GPS coordinates to actual road networks, find nearest segments, reconstruct paths, and pull legal speed limit data.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Google Roads MCP

Get Nearest Roads

Finds the nearest existing road segment and its unique ID for up to 100 individual GPS coordinates, treating each point separately.

Snap To Roads

Matches a continuous sequence of GPS points (up to 100) to the most likely road path...

Get Snapped Speed Limits

Performs both road snapping and speed limit retrieval simultaneously, providing...

Get Speed Limits

Retrieves the specific legal speed limits (km/h) for any known road segment using...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Google Roads MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Google Roads integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Google Roads, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
Google Roads MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Google Roads. 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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The frustration of raw GPS data

Every time you pull a log file from a vehicle or run a survey that uses GPS coordinates, you get thousands of numbers. But those numbers are just points floating in space; they don't tell you if the point is actually on a drivable road, what speed limit applies there, or how to draw a clean path between them. You spend hours cleaning up noise and guessing at geometry.

With this MCP, your AI agent handles that entire process. It takes those raw numbers and reliably converts them into usable road geometries, identifying the exact segment and associated place ID for every point you give it. Your output isn't just data; it’s a validated map.

Getting speed limit context with Google Roads

Before this, figuring out the legal speed on a segment required multiple steps: first finding the road geometry, then taking the resulting ID to another service just for the limits. This was slow, complex, and prone to breaking if any step failed.

Now, you execute `get_snapped_speed_limits`. It handles both the mapping and the legal data retrieval in a single pass. The difference is simple: you get actionable compliance reports without building custom multi-step API wrappers.

What Google Roads MCP does for your AI

This MCP lets your AI client take control of complex geospatial tasks that usually require dedicated GIS software. Instead of struggling with noisy GPS feeds or guessing where a track went, you can pass raw coordinate data and get clean road geometries back. You'll find tools to snap entire tracks to the most likely roads traveled, identifying every point along the way.

It also helps you figure out which major roads are near individual points, even if they aren't on a path. Plus, it retrieves posted speed limits for those identified segments. Because Vinkius hosts this MCP, your agent can access all these advanced mapping capabilities—from snapping paths to getting specific place IDs—all through one conversation.

Built · Hosted · Managed by Vinkius Google Roads - Map GPS Tracks to Road Geometry
Server ID 019d75a9-2756-70ad-b4d4-1926602cfa5f
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about Google Roads MCP

How does Google Roads MCP handle gaps in GPS tracks? +

The snap_to_roads tool reconstructs the path by interpolating points between your input coordinates, creating a smoother, more continuous road geometry than raw data allows. This helps visualize the intended travel route.

Can I use Google Roads MCP for individual point analysis? +

Yes. If you have scattered GPS points that don't form a clear path, get_nearest_roads treats each coordinate independently to find its closest road segment and associated place ID.

What is the difference between snap_to_roads and get_snapped_speed_limits? +

snap_to_roads only returns the clean geometry and place IDs. get_snapped_speed_limits, however, performs both functions in a single call, giving you the speed limit data along with the mapped path.

Does Google Roads MCP require continuous GPS data? +

No. It supports both continuous paths using snap_to_roads and discrete points using get_nearest_roads, making it versatile for various data collection scenarios.