Google Roads MCP. Map raw GPS tracks to real-world road data.

Look, you gotta get your AI client connected here if you wanna handle geospatial data right. This server gives your agent complete control over mapping GPS tracks to actual roads worldwide. It's not just about drawing a line on a map; it's about understanding the underlying road geometry, finding precise street segments, and pulling official speed limit data for anything you track.

If you're dealing with raw GPS feeds—maybe some noisy telemetry from a fleet or a detailed historical route—this stack cleans that up so your agent can use it. You'll learn how to match coordinates to real-world roads using the available tools, and you won't be sending redundant calls back and forth.

Here’s what you do with these specific functions:

Mapping a Continuous Route: When you have a long string of GPS coordinates that represent a continuous journey, use snap_to_roads. This function matches the whole path to the most likely real-world roads traveled. The output isn't just a rough line; it generates clean geometry and gives you Place IDs for those segments.

Plus, you can set interpolation when calling this tool if you need to smooth out the path before you use it.

Finding Single Points on the Map: But what if your data is disconnected? Say you got 50 random GPS points scattered across a city—you don't want to treat them like one long trip. For those isolated coordinates, use get_nearest_roads. This tool finds the closest road segment for up to 100 individual points.

It treats every single point independently of the others, giving you the place ID and confirming which local street or road section is geographically nearest.

Getting Speed Limits and Geometry in One Go: If speed limits are critical, don't waste an API call jumping between two tools. You can use get_snapped_speed_limits. This single function snaps your GPS points to actual roads while simultaneously grabbing the posted speed limit. It returns everything you need—the snapped points, your original coordinates, the resulting Place IDs, and the measured speed limit—all in one call.

Targeting Specific Speed Limits: Once you’ve used any of the mapping tools above and generated a unique Google Place ID for a specific road segment, use get_speed_limits. This lets your agent pull only the official posted speed limit data (in kilometers per hour) linked directly to that specific place ID.

You don't need coordinates; you just need the ID.

The Workflow: Generally, you’ll take a series of GPS points and run them through snap_to_roads or get_snapped_speed_limits. The output from those initial calls gives your agent the vital Place IDs. You then use those resulting Place IDs—which are unique identifiers for road segments—with get_speed_limits to pull specific attributes, like the speed limit.

If you're dealing with single points and need that ID, run them through get_nearest_roads. The entire process lets your agent convert raw, messy GPS coordinates into clean, actionable road geometry and associated metadata. You don't have to stitch together multiple services; this gives you everything under one roof.