# Computer Vision Defect Detection API

> Computer Vision Defect Detection API is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.3/call, status unknown (last checked 2026-09-15).

Analyzes images or visual data to detect and identify defects using computer vision techniques

## Facts

- Endpoint: POST https://api.m2mcent.com/computer-vision-defect-mcp/api/process
- Price: $0.3/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/computer-vision-defect-detection-api-f0da6a44
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_GImLasSX2CwAVE5KwQCto

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 computer-vision-defect-detection-api-f0da6a44 -d '<json body>'
```

Example prompt: Inspect this product image for any visible defects or surface anomalies and tell me what issues you find.

## When to prefer this

Use this endpoint when you need automated, AI-powered visual defect detection on image data within an agentic workflow, particularly when integrating quality control into a pipeline that handles manufacturing, logistics, or product inspection at scale. Prefer this over manual inspection workflows or general-purpose vision models when you need a dedicated defect-classification signal with per-call pay-as-you-go pricing.

## Known failure modes

- Invalid or missing data field returns an error
- Non-image or unparseable data string causes processing failure
- Low-resolution or corrupted image may result in no defects detected or low confidence
- Payment not received results in HTTP 402 response
- Unsupported image format may cause processing error

## 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 a structured analysis of the submitted visual data, including identified defects, their locations or descriptions, defect types, and confidence scores indicating the likelihood and severity of each detected issue.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "payload": {
   "type": "string"
  }
 }
}
```

## Response schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/computer-vision-defect-detection-api-f0da6a44/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)