# LiDAR 360° Collision Detection MCP

> LiDAR 360° Collision Detection MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.25/call, status unknown (last checked 2026-10-14).

Processes LiDAR point cloud or sensor data to detect 360-degree collision risks and proximity hazards around an agent or vehicle.

## Facts

- Endpoint: POST https://api.m2mcent.com/lidar-360-collision-mcp/api/process?utm_source=zero.xyz
- Price: $0.25/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/lidar-360-collision-detection-mcp-3001ad0f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_n_CSqTsphQ_AwGsGISEB4

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability lidar-360-collision-detection-mcp-3001ad0f -d '<json body>'
```

Example prompt: Can you process this LiDAR scan data and tell me if there are any collision risks or obstacles detected in the 360-degree field around my robot?

## When to prefer this

Choose this endpoint when you need to process raw LiDAR or point-cloud sensor data for full 360-degree collision and obstacle detection, especially in robotics, autonomous navigation, or spatial safety contexts where comprehensive perimeter awareness is required.

## Known failure modes

- Malformed or empty 'data' string returns validation error
- Unrecognized data format produces unparseable result
- Sensor data too sparse or noisy leads to low-confidence detections
- Oversized payload may time out or be rejected
- Missing required 'data' field returns 400 bad request

## How this service works

The premier global index of 1,069 monetized MCP nodes across 205 specialized subdomains. Gasless USDC runtime settlements via x402 V2 Spec on Base L2. Save 95% token context.

## Output

Returns collision detection results derived from the submitted LiDAR data, including identified obstacles, their positions relative to the sensor origin, proximity distances, and assessed collision risk levels across the 360-degree scan field.

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "success": true
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/lidar-360-collision-detection-mcp-3001ad0f/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.m2mcent.com](https://www.zero.xyz/host/api.m2mcent.com/llms.txt)