# Google Roads MCP

> 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.

## Overview
- **Category:** industry-titans
- **Price:** Free
- **Tags:** gps-tracking, map-matching, road-geometry, speed-limits, telemetry

## Description

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.

## Tools

### 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 and generates smoothed geometry with unique IDs.

### get_snapped_speed_limits
Performs both road snapping and speed limit retrieval simultaneously, providing matched coordinates and current posted limits in one call.

### get_speed_limits
Retrieves the specific legal speed limits (km/h) for any known road segment using its place ID.

## Prompt Examples

**Prompt:** 
```
Snap these GPS coordinates to roads: 40.7128,-74.0060|40.7135,-74.0055|40.7142,-74.0048
```

**Response:** 
```
Snapping GPS coordinates to roads... 3 points snapped successfully. Point 1: Original (40.712800, -74.006000) -> Snapped to (40.712820, -74.005980), placeId: ChIJd8BlQ2BZwokRAFUEcm_qrcA. Point 2: Original (40.713500, -74.005500) -> Snapped to (40.713510, -74.005490), placeId: ChIJd8BlQ2BZwokRAFUEcm_qrcB. Point 3: Original (40.714200, -74.004800) -> Snapped to (40.714190, -74.004810), placeId: ChIJd8BlQ2BZwokRAFUEcm_qrcC. All points snapped to Broadway in Lower Manhattan. Would you like speed limit data for these road segments?
```

**Prompt:** 
```
Get speed limits for these place IDs: ChIJd8BlQ2BZwokRAFUEcm_qrcA|ChIJd8BlQ2BZwokRAFUEcm_qrcB
```

**Response:** 
```
Fetching speed limits... 2 road segments found. Segment 1: placeId ChIJd8BlQ2BZwokRAFUEcm_qrcA, speed limit 40 km/h (25 mph), road name Broadway, New York NY. Segment 2: placeId ChIJd8BlQ2BZwokRAFUEcm_qrcB, speed limit 40 km/h (25 mph), road name Broadway, New York NY. Both segments are in a downtown urban zone with reduced speed limits.
```

**Prompt:** 
```
Find the nearest road to these coordinates: 34.0522,-118.2437 and 34.0530,-118.2445
```

**Response:** 
```
Finding nearest roads... Point 1 (34.0522, -118.2437) snapped to Spring Street, Los Angeles CA, placeId: ChIJYWRSrVHHwoARpVl2b3cFzQE. Point 2 (34.0530, -118.2445) snapped to Broadway, Los Angeles CA, placeId: ChIJYWRSrVHHwoARpVl2b3cFzQF. Both points are in downtown Los Angeles within 15 meters of major roads. Would you like speed limits for these road segments?
```

## Capabilities

### 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.

## Use Cases

### Analyzing Driver Compliance
A fleet safety analyst needs to audit a driver's route. Instead of manually cross-referencing GPS logs with local maps, the agent uses `snap_to_roads` to map the path and then feeds those resulting place IDs into `get_speed_limits`. This instantly generates a report showing every segment where the recorded speed violated the posted limit.

### Mapping Field Data Collection
A GIS professional collects GPS points across an area but doesn't have a continuous path. They use `get_nearest_roads` to snap each individual point cluster to its nearest road segment, allowing them to map the entire collection accurately for later spatial analysis.

### Building Real-Time Vehicle Dashboards
A developer needs a dashboard that shows both a vehicle's current location and the legal speed limit. They use `get_snapped_speed_limits` to get this combined data in one API call, ensuring the visualization is always accurate and up-to-date.

### Reconstructing Historical Routes
A mapping developer needs to clean up years of archived GPS telemetry from a vehicle. They pass the raw data into `snap_to_roads` which smooths out all the signal noise and reconstructs the true, navigable road path for accurate visualization.

## Benefits

- Accurate Route Reconstruction: Use `snap_to_roads` to turn messy, noisy vehicle tracks into clean, continuous road geometries for visualization and historical analysis.
- Efficiency Gains with Combined Calls: The `get_snapped_speed_limits` tool eliminates the need for multiple API calls; it gives you both the snapped location and the speed limit in one request.
- Targeted Point Analysis: When you only have scattered points, use `get_nearest_roads`. This function treats each coordinate independently to find the closest road segment without assuming a path exists between them.
- Compliance Monitoring: By pairing `snap_to_roads` with `get_speed_limits`, you can programmatically check if recorded speeds match posted legal limits for specific segments.
- Data Foundation: The resulting place IDs are reusable. You can take the output from any snapping tool and feed it directly into other mapping services to enrich your data.

## How It Works

The bottom line is that you stop worrying about API keys and complex parameters; your agent just asks for what it needs—a clean map or a speed check—and gets a structured answer.

1. Subscribe to this MCP and provide your Google Maps Platform API key, ensuring the Roads API is enabled.
2. Your AI client sends raw GPS coordinates or a sequence of points it needs mapped against actual roads.
3. The MCP processes the data, returning snapped road geometries, associated place IDs, and optional speed limit values.

## Frequently Asked Questions

**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.