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Visual QA Frame Analyzer MCP
x402
Visual QA Frame Analyzer MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-15).
Analyzes video frames or images to answer visual question-answering (QA) tasks, extracting meaning and answering questions about visual content.
Price / call$0.1
Success—
StatusUnknown
How this service works
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Output
Returns a structured response containing answers to visual questions about the submitted image or video frame, including descriptions of objects, scenes, actions, and other visual elements detected in the data.
Example use cases
Security footage frame inspection
“I have a frame from a security camera — can you analyze it and tell me how many people are visible, what they're wearing, and whether anyone appears to be carrying a bag?”
Product image content verification
“Here's an image of one of our product listings — analyze the frame and tell me if the product label, color, and packaging match what you'd expect for a premium coffee blend.”
Video scene description for accessibility
“I have a still frame from a documentary video — describe everything visible in the scene so I can generate an accessibility caption for visually impaired viewers.”
Technical details
Endpoint
POSThttps://api.m2mcent.com/visual-qa-frame-analyzer-mcp/api/processWhen to prefer
Choose this endpoint when you need to perform visual question answering on individual image or video frames — particularly useful in agentic pipelines where visual content must be interpreted programmatically without a human in the loop. Prefer this over general image description APIs when you need targeted QA-style answers about specific visual elements in a frame.
Side effects
- Invalid or malformed base64 image data returns an error
- Unsupported image format may cause processing failure
- Extremely low-resolution or blank frames may yield low-confidence or empty results
- Payment failure (402) if USDC balance insufficient
- Timeout on very large image payloads
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| payload | string |
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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